KR20120011678A - Frequency Reconfigurable Digital Filter and Equalizer Using the Same - Google Patents

Abstract

PURPOSE: A digital filter capable of frequency reconstruction and an equalizer using the same are provided to change parameter using a closed-form response in a time area. CONSTITUTION: An up sampling unit(400) applies sampling kernel scaled with the sampling phase number to a model filter. The multi image forming unit(402) creates multi images corresponding to the up-sampled model filter response. The multi complimentary image forming unit(404) creates multi complimentary images in a frequency domain opposed to the passing band of the multi images corresponding to the up-sampled model filter response. An image response operation unit(406) computes the response to the selected image or the complimentary image. A filter response operation unit(408) adds up the image response to each selected image and calculates the final filter response.

Description

Frequency Reconfigurable Digital Filter and Equalizer Using the Same}

The present invention relates to a digital filter and an equalizer using the same, and more particularly, to a digital filter capable of reconstructing a pass band of a filter and an equalizer using the same.

Digital filters have many advantages compared to analog filters because they can be integrated circuits and can be miniaturized, low cost, and high in reliability. In particular, as the communication speed, high speed, and the amount of communication increase, the field of application of the digital filter is increasing, and it is used in places such as the transmitting end and the receiving end of the baseband part of the mobile communication system.

Digital filters are generally divided into finite impulse response (FIR) filters and infinite impulse response (IIR) filters.

The finite impulse response filter uses the property that the impulse response will be of finite length when it is input to the filter because the finite impulse response filter does not use any feedback.

Finite impulse response filters that do not use feedback do not require a feedback loop to ensure stability. In particular, since the specification of the linear phase characteristic is satisfied, it is widely used for applications such as waveform transmission. However, when the finite impulse response filter tries to obtain the amplitude characteristic that is the same as that of the infinite impulse response filter, the order becomes larger, which causes more burden on hardware such as an adder and a multiplier.

When designing a finite impulse response filter, there are two design methods in the frequency domain and a design method in the time domain, and a window function method and a frequency sampling method are frequently used when designing in the frequency domain.

On the other hand, when designing in the time domain, the impulse response corresponds to the coefficients of the finite impulse response filter, which is simpler than the design in the frequency domain, and there are many known linear programming methods to approximate the transfer function. The optimal solution can be found.

In particular, the finite impulse response filter allows so that calculations whose finiteness of their outputs do not produce decimated outputs, or calculations with predictable values in interpolated outputs, are omitted, so called multirate. ) Is computationally efficient in applications, for example when interpolated or decimated to raise or lower the sampling rate of a signal.

Finite impulse response filter has a problem that it is very difficult to reconstruct the band pass characteristics when the number of taps, filter coefficients, etc. is designed to have a specific pass band.

7 is a diagram illustrating an example of a filter for reconstructing a frequency by changing a conventional filter coefficient.

Referring to FIG. 7, a frequency reconstruction filter according to a conventional example includes a coefficient storage unit 100, a multiplexer 102, a multiplier 104, and an adder 106. The coefficient storage unit 100 of the conventional reconstruction filter stores coefficient information for a plurality of pass bands.

By extracting the coefficient information according to the user's band selection and providing it to the multiplexer 102 so that the filter impulse response corresponding to the selected band can be generated, the generated filter impulse response is the input function (x (n)) The output signal y (n) is generated by filtering the input function.

Such a conventional method has a limitation in a band that can be reconstructed, and even if frequency reconstruction is performed, only the coefficients of the filter are changed, so that proper reconstruction is difficult to be achieved.

In addition, frequency reconstruction is not possible for frequency bands other than the pre-stored filter coefficients, and since the filter coefficients must be stored for frequency reconstruction, a large amount of information storage space is required.

In recent years, the use of equalizers for hearing aids and sound source reproduction has become commonplace, and in such an equalizer, reconstruction of a passband that matches a user's preference is one of the important functions. Is required.

The present invention proposes a digital filter capable of frequency reconstruction so as to have various band pass characteristics with only a small number of parameter changes, and an equalizer using the same.

In addition, the present invention proposes a digital filter freely reconfigurable for various bands and a digital filter using the same.

In addition, the present invention proposes a digital filter capable of frequency reconstruction through a plurality of image combinations so that the user can easily change the band of the filter.

Furthermore, the present invention proposes a digital filter capable of frequency reconstruction in which a band pass characteristic can be changed by a simple parameter change through a closed-form response in the time domain in a specific band.

Other aspects of the present invention will be readily apparent to those skilled in the art through the following examples.

According to an aspect of the invention, the model filter response storage for storing model filter information; A sampling kernel storage unit applied to the model filter response and scaled by a sampling constant to upsample the model filter response, and generating a multi-image repeated with a predetermined period with respect to the upsampled model filter response; A complimentary conversion unit for generating a multi-complementary image having the same characteristics as that of the multi-image and repeating the predetermined period in a frequency region in which the multi-image is not generated; There is provided a digital filter capable of frequency reconstruction including an image response calculator for calculating a response of the multi-complementary image and an image corresponding to a selected band of the multi-image.

The digital filter may further include a filter response calculator configured to generate a filter response by summing responses of each image or the complementary image of the selected band when the selected band corresponds to a plurality of multi-images or multi-complements. have.

And the sampling kernel includes a sampling constant and a multi-image number as variables.

)은 다음의 수학식을 포함할 수 있다. The sampling kernel (

) May include the following equation.

In the above equation, L is a multi-image number and α is a sampling constant.

Upsampling a model filter response by applying the sampling kernel and generating a plurality of multi-images may be performed by the following equation.

은 기저 대역의 필터 응답이고, L은 이미지 번호 이며,

는 샘플링 커널이고, 멀티 이미지의 수는 L 값에 상응함. Α is the sampling constant in the above equation,

Is the baseband filter response, L is the image number,

Is the sampling kernel, and the number of multi-images corresponds to the L value.

만큼 지연시켜 다수의 멀티 컴플리멘터리 이미지를 생성한다. The complimentary converter is configured to generate a multi-image response in a z domain.

Delay by to create multiple multi-complementary images.

The image response calculator is configured to generate (L-1) images or the complimentary images from the response for generating the L images or the complementary images for the response operation of the selected L-th image or the complementary image. Compute the image response by subtracting the response to generate.

The repetition period of the multi-image and the multi-complementary image corresponds to the bandwidth of the upsampled model filter response.

According to another aspect of the present invention, an upsampling unit for performing upsampling to apply a sampling kernel scaled by a sampling constant to a model filter; A multi-image generator for generating L multi-images that are repeated with a predetermined period with respect to the upsampled model filter response; A multi-complementary image generator for generating a multi-complementary image having the same characteristics as the multi-image with the predetermined period in a frequency region where the multi-image is not generated; And an image response calculator configured to calculate a response of the multi-complementary image and an image corresponding to a selected band of the multi-image.

According to another aspect of the invention, the channel setting unit for setting the channel to be used according to the number of channels and channel information selected by the user; A gain setting unit for setting gain information of each channel; A frequency reconstruction unit configured to set a response of each channel based on the set number of channels and channel information; And an equalizer for generating an equalizer output by applying the channel gain setting information to the filter response of the frequency reconstructing unit, wherein the frequency reconstructing unit includes: a model filter response storage unit for storing model filter information; And a sampling kernel storage scaled by a sampling constant to upsample the model filter response, and repeating with a predetermined period for the upsampled model filter response and generating a plurality of multi-images based on the number of channels. The complimentary conversion unit for generating a plurality of multi-complementary images based on the number of channels and having the same characteristics as the multi-images, repeated in the frequency region where no multi-images are generated, the multi-com Lines of fleece images and the multi-image An equalizer is provided that includes an image response calculator that calculates a response of an image corresponding to the selected channel.

According to another aspect of the invention, the channel setting unit for setting the channel to be used according to the number of channels and channel information selected by the user; A gain setting unit for setting gain information of each channel; A frequency reconstruction unit configured to set a response of each channel based on the set number of channels and channel information; And an equalizer unit configured to generate an equalizer output by applying the channel gain setting information to the filter response of the frequency reconstructor, wherein the frequency reconstructor performs upsampling to apply a sampling kernel scaled by a sampling constant to a model filter. An upsampling unit performing a predetermined period with respect to the upsampled model filter response and generating L multi-images based on the number of channels, in the frequency domain in which the multi-images are not generated; A multi-complementary image generator for generating L multi-complementary images having the same characteristics as the multi-images with a predetermined period and based on the number of channels, and the multi-complementary images and the multi-images Response of the image corresponding to the selected channel The equalizer comprises an operational unit for image response are provided.

According to an embodiment of the present invention, there is an advantage in that frequency reconstruction is possible to have various band pass characteristics with only a small number of parameter changes.

In addition, the present invention has the advantage that the frequency can be freely reconfigured for various bands, the user can easily change the band of the filter.

Furthermore, the present invention has the advantage that the band pass characteristic can be changed by simple parameter change through a closed-form response in the time domain in a specific band.

1 is a diagram illustrating a change in model filter response when upsampling is performed according to an embodiment of the present invention.
2 illustrates an example of a multi-image and multi-complementary image generated in accordance with one embodiment of the present invention.
3 is a diagram illustrating a change of a multi image according to a change of an L value according to an embodiment of the present invention.
4 is a block diagram showing the configuration of a digital filter capable of frequency reconstruction according to the first embodiment of the present invention.
5 is a block diagram showing the configuration of a digital filter capable of frequency reconstruction according to a second embodiment of the present invention.
6 is a block diagram showing the configuration of an equalizer using a frequency reconfigurable filter according to an embodiment of the present invention.
7 illustrates an example of a filter for reconstructing a frequency by changing a conventional filter coefficient.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description with reference to the accompanying drawings, the same or corresponding components will be given the same reference numerals and redundant description thereof will be omitted.

How the Filter Works

(1) upsampling

The filter of the present invention performs upsampling on the model filter. The model filter may be implemented in hardware or software as a filter function designed to have specific filtering characteristics. According to a preferred embodiment of the present invention, a half-band filter can be used as a model filter, and the half-band filter has characteristics suitable for being applied to an equalizer.

In the present invention, upsampling is performed to improve a skirt characteristic corresponding to a slope of a pass band among characteristics of a filter, and additionally, bandwidth may be adjusted through upsampling. Upsampling is also an outpost required to generate the multi-image and multi-complementary images of the present invention described later.

Designing a good skirt characteristic (large passband slope) is the ideal filter design, but to improve the skirt characteristic, a large number of coefficients must be applied to the filter design, which requires a large number of taps on the filter. It means to be done.

Increasing the number of taps on a filter means that the filter's price and size increase when the filter is manufactured in hardware, and that a large amount of computation is required when the filter is implemented in software. (Trade Off) relationship.

In the present invention, upsampling is performed on a model filter function having a relatively small number of taps to improve the skirt characteristics and to adjust the bandwidth of the model filter as necessary.

According to a preferred embodiment of the present invention, upsampling is done using a sampling kernel scaled by the sampling constant α.

라고 정의하고 α를 샘플링 상수로 정의하고, 길이가 N인 유한 임펄스 응답 필터 응답을

이라 할 때, 본 발명에 의한 샘플링 상수에 의해 스케일링되는 업샘플링은 다음의 수학식 1과 같이 수행될 수 있다.Sampling kernel

Define α as the sampling constant, and define a finite impulse response filter

In this case, the upsampling scaled by the sampling constant according to the present invention may be performed as in Equation 1 below.

은 업샘플링에 의해 최종적으로 양호한 스커트 특성을 가지는 필터 응답이다. In Equation 1 above

Is the filter response which finally has good skirt characteristics by upsampling.

Meanwhile, in Equation 1, the sampling kernel may have various forms. In one of the most ideal cases, the sampling kernel may have the form of a sinc function, but is not limited thereto. It will be apparent to those skilled in the art that various types of functions may be applied to the sampling kernel.

For example, including the Sinc function as shown in Equation 2 below. It may have various types of adaptive window functions, and various functions may be applied in addition.

In Equation 2 above, the first equation is a raised-cosine, where R is a roll-off constant and is a criterion for determining the bandwidth of the filter. In Equation 2, the second equation is Kaiser, where I ₀ is a _zeroth order modified Bessel function of the first kind, β is a random real number that determines the shape of the window, and M is the length of the sequence.

The third formula uses Dolph-Chebychev. In the third equation, λ is a side-lobe adjustable parameter.

1 is a diagram illustrating a change in model filter response when upsampling is performed according to an embodiment of the present invention.

In FIG. 1, (a) shows the response of the model filter before upsampling, and (b) shows the filter response after the upsampling.

Referring to FIG. 1, when compared with the model filter function before upsampling, the transition slope in the pass band and the stop band is increased, indicating that the skirt characteristic is improved.

When an integer is used as the sampling constant α in Equation 1, Equation 1 may be expressed in a convolution form as shown in Equation 3 below. In other words, by performing upsampling by simple convolution operation, the amount of computation can be reduced compared to the existing filter design.

은

의 인접한 필터 계수 사이에 (α-1)개의 0을 끼워넣는 형태로 변경되고, 수학식 3에서와 같이 실제 연산은 h[n]의 계수만으로 이루어지므로 샘플링 레이트나 계산량이 증가하지는 않는다. In the upsampling scheme according to the present invention

silver

(Α-1) zeros are interposed between adjacent filter coefficients, and as shown in Equation 3, since the actual operation is performed only with the coefficient of h [n], the sampling rate or the amount of calculation does not increase.

는 통과 대역의 주파수이고

는 저지 대역의 주파수이다. 이때 얻어진 샘플링 상수에 가장 근사한 정수를 α로 결정하여 적용하는 것이 전체적인 연산에 있어 가장 큰 효율을 보일 수 있다. On the other hand, in setting the sampling constant α, the optimum sampling constant can be obtained to have an optimal calculation amount. Equation 4 below is an example for obtaining an optimal sampling constant.

Is the frequency of the passband

Is the frequency of the stopband. In this case, determining and applying an integer closest to the obtained sampling constant as α may show the greatest efficiency in the overall operation.

(2) multi-image and multi-complementary images

The filter of the present invention generates multiple multi-images for the upsampled filter response to select various passbands. The term "image" used in the present invention refers to an object forming a specific pass band in the frequency domain graph of the filter, and may be interpreted as the same meaning as the specific band.

The model filter response generally has a filtering response for the baseband, so the upsampled model filter response has only one image in the low frequency band.

In the present invention, the up-sampling filter response having a single image has a function of converting to have multiple images, which means that the filter response has a plurality of passbands through such conversion.

Multiple multi-images are generated based on the baseband image, and the multiple images (multiple passbands) have the same characteristics as those of the miraculous band. That is, when the low pass band image has a bandwidth of W, a skirt characteristic of C, and a size of A, a plurality of formed multi-images also have the same characteristic of having a bandwidth of W, a skirt characteristic of C, and A of size.

The multiple images generated based on the low pass band image have a certain period, where the period is related to the bandwidth of the low pass band image.

For example, when a low pass band image has a bandwidth of 2W from -W to W, the multi images are repeatedly formed in the same form as the low pass image with a period of 2W.

Thus, when there is a low pass band image with a bandwidth of 2W from -W to W, a second multi-image is generated in the 3W to 5W band, and a third multi-image in the 7W to 9W band is generated. Images are created.

2 is a diagram illustrating an example of a multi-image and a multi-complementary image generated according to an embodiment of the present invention.

In FIG. 2, (a) shows the response of Equation 3 in the frequency domain, and (b) shows multiple images for the response of (a). As shown in Fig. 2, the same image as the model filter response is repeatedly formed with a constant period.

Generating a plurality of multi-images for the model sample response of the upsampled miracle band may be implemented by performing a kind of IDTFT transform, which is expressed by Equation 5 below.

은 다음의 수학식 6과 같이 표현될 수 있다. In Equation 5 above, the single low pass filter may be extended to have a desired number of images. When L is the number of images (image number), it is a filter response that has multiple multi-images by IDTFT transform.

May be expressed as Equation 6 below.

에 Sinc 함수가 적용될 경우 샘플링 커널은 다음의 수학식 7과 같이 표현될 수 있다. In Equation 6 above, the sampling kernel

When the Sinc function is applied to, the sampling kernel may be expressed as in Equation 7 below.

In the above equations (6) and (7), if L is 0, the multi-image is not generated. If L has other integer values, the multi-image corresponding to the integer is generated.

If Equation 6 is expressed as a frequency response, it may be expressed as Equation 8 below.

As mentioned above, the shape of such multi-images is the same as the upsampled model filter response, the period of which corresponds to the bandwidth of the upsampled model filter response.

3 is a diagram illustrating a change of a multi image according to a change of an L value according to an embodiment of the present invention.

Referring to FIG. 3, the generation of the multi-image may perform the IDTFT operation on the upsampled model filter response, but may adjust the number of the multi-images generated by adjusting the image number L. FIG.

As shown in FIG. 3, when L is 1, one additional multi-image is generated, and when L is 3, three additional multi-images are generated. In this case, L may be selected by the user.

Meanwhile, in the present invention, a plurality of complimentary images are generated in a frequency region opposite to the multi image separately from the multi image based on the baseband image.

That is, the complimentary image refers to an image formed in a frequency region in which no multi-image is formed. Referring to FIG. 2, a multi-complementary image in a W-3W region and a 5W-7W region in which the multi-image is not formed An image is formed.

The multi-complementary image also has the same characteristics as the low pass image by the model response, and is formed repeatedly with the same period as the bandwidth of the low pass image.

만큼 지연시킴으로써 획득할 수 있으며(여기서 N은 모델 필터의 길이임), 이는 다음의 수학식 9와 같이 표현될 수 있다. Multi-complementary images produce model filter responses in the z domain

It can be obtained by delaying (where N is the length of the model filter), which can be expressed as Equation 9 below.

Finally, the multi-complementary image may be obtained through Equation 10 below, and the number of multi-complementary images may also be determined by the L value.

When the Sinc function is applied as the sampling kernel for the multi-complementary image in Equation 10, the sampling kernel may be expressed as Equation 11 below.

In addition, if Equation 10 is expressed as a frequency response, it may be expressed as Equation 12 below.

(3) image response operation

When the multi-image and the multi-complementary image are generated through Equations 6 and 10, a process of setting a response to the pass band is performed by selecting an image corresponding to the pass band.

The user selects an image or multi-complementary image corresponding to a desired passband among a plurality of multi-images and multi-complementary images to calculate a response of each image.

For example, if a band pass filter for a band of 7W-9W is needed, it is the same band as the second multi-image in FIG. 3 and generates a filter response for the second multi-image.

The filter response for the selected N-th multi-image may be obtained by subtracting the equation of L = (N-1) from the equation of L = N in Equation 6, which is the filter response for the multi-image. In the above example, the filter response for the second multi-image may be obtained by subtracting the response of Equation 6 set to L = 1 from the response of Equation 6 set to L = 2.

The filter response corresponding to the L th image may be expressed by Equation 13 below.

The same applies to obtaining a filter response for a specific multi-complementary image.

The filter response for the L-th multi-complementary image may be obtained by subtracting the expression L-1 from Equation 10 in Equation 10, which may be expressed as Equation 14 below.

(4) final filter response

The present invention sums the filter response for each selected image or complementary image to produce the final filter response. When a wideband filter response or filter response for multiple bands is required, multiple images or complimentary images are selected, and the final filter response is obtained by summing the filter responses of each image or complementary image.

For example, when a multiband pass filter corresponding to each of the second and third images of the multi-image is required, the final filter response can be obtained by summing filter responses of each of the second and third images. .

Filter composition

(1) First Embodiment

4 is a block diagram showing the configuration of a digital filter capable of frequency reconstruction according to the first embodiment of the present invention.

Referring to FIG. 4, the digital filter capable of frequency reconstruction according to the first embodiment of the present invention may include an upsampling unit 400, a multi-image generator 402, a multi-complementary image generator 404, and an image. It may include a response operator 406 and a filter response operator 408.

The upsampling unit 400 applies the sampling kernel scaled by the sampling constant to the model filter to improve the characteristics of the model filter. Upsampling for the model filter may be performed by multiplying the sampling kernel scaled by the sampling constant α with respect to the model filter function as in Equation 1, and the skirt characteristic and the bandwidth of the filter change according to the sampling constant α value. α can be appropriately selected according to the bandwidth and skirt characteristics desired by the user.

The multi-image generator 402 generates a multi image corresponding to a plurality of pass bands with respect to the upsampled model filter response, and the multi-complementary image generator 404 generates a multi-image with respect to the upsampled model filter response. Generate multiple multi-complementary images in the frequency domain opposite to the pass band of.

As described above, the multi-image and multi-complementary image have the same characteristics as the upsampled model filter response but form passbands in different frequency domains.

The multi-image may be generated through a transform, such as Equation 6, for the upsampled model filter response, and the multi-complementary image may be generated by using a complimentary transform or an equation 10, such as Equation 9. Can be.

In the first embodiment, the upsampling and the generation of the multi-image and the multi-complementary image are described as a sequential process, but the upsampling and the multi-image and the multi-computation are performed using Equation 6, 9 or 10. It will be apparent to those skilled in the art that the generation of the flimentary image can be made at one time.

The image response calculator 406 calculates a response to an image or a complementary image selected by the user. When the user selects a desired passband from a plurality of multi-images or multi-complementary images, the image response calculator 406 calculates a response to each selected image.

As described above, the filter response for the image can be obtained by subtracting the response equation transformed to generate the multi-image up to the (L-1) th to the L-th response. Each image response to the multi-complementary image is represented by Equations 13 and 14, respectively.

The filter response calculator 408 calculates the final filter response by summing the image responses for each selected image, thereby obtaining a frequency-reconstructed filter response in a closed-form form. If only one image is selected, it is the final filter response of the image, and no separate summing process is required.

(2) Second Example

5 is a block diagram showing the configuration of a digital filter capable of frequency reconstruction according to a second embodiment of the present invention.

The second embodiment is a module representation of the filter configuration when the filter according to the embodiment of the present invention is implemented in software. The filter of the first embodiment is represented in a block diagram from another viewpoint.

Referring to FIG. 5, the digital filter capable of frequency reconstruction according to the second embodiment of the present invention includes a model filter response storage unit 500, a sampling kernel storage unit 502, a complimentary transform unit 504, and an image. The response operator 506 and the filter response operator 508 may be included.

The model filter response storage unit 500 stores a model filter response having a specific tap number and coefficient.

The sampling kernel storage unit 502 stores a sampling kernel response that is scaled by sampling constants applied to upsampling and multi-image generation and has an image number L as a variable. When the Sinc function is used as the sampling kernel, a sampling kernel such as Equation 7 may be stored in the sampling kernel storage unit 502, and various sampling kernels as illustrated in Equation 2 may be utilized in addition to the Sinc function.

The complimentary converter 504 performs a complimentary transform for generating a multi-complementary image. Complementary conversion may be performed through a conversion equation such as Equation 9, or a multi-complementary image may be generated by separately storing a model filter response and a sampling kernel for the complimentary image.

The image response calculator 506 calculates an image response to an image or a complimentary image number selected by the user. When the multi image is selected, the filter response corresponding to the selected image is calculated by using the stored model filter response and the sampling kernel including the stored sampling constant and the image number as variables in the same manner as in Equations 6 and 13.

In addition, when a specific complimentary image is selected among the multi-complementary images, the equation 10 and the equation are converted through a sampling kernel and a complimentary conversion using the stored model filter response, the stored sampling constant, and the image number as variables. In the same way as in step 14, the filter response corresponding to the selected complementary image is calculated.

The filter response calculator 508 calculates the final filter response by summing the image responses for each selected image, thereby obtaining a frequency-reconstructed filter response in a closed-form form. If only one image is selected, it is the final filter response of the image, and no separate summing process is required.

Equalizer with Filter

By using the frequency reconfigurable digital filter of the present invention described above, it is possible to implement an equalizer capable of adjusting gain and band pass characteristics for a plurality of frequency bands. Equalizers can also be used to adjust the output characteristics of sound sources in digital devices capable of playing music (e.g. mobile phones, MP3 players, computers, laptops, etc.), and in personalizing devices according to the user's hearing characteristics in devices such as hearing aids. It can also be used when making hearing aids.

6 is a block diagram showing the configuration of an equalizer using a frequency reconfigurable filter according to an embodiment of the present invention.

Referring to FIG. 6, an equalizer according to an embodiment of the present invention includes a channel setting unit 600, a gain setting unit 602, a GUI unit 604, a frequency reconstruction unit 606, and an equalizer unit 608. ) May be included.

The GUI unit 604 provides an interface for the user to select the pass band and channel of the equalizer. Through the graphical interface provided by the GUI unit 604, the user can set the channel of the equalizer and the gain information of each channel. A device with a display such as a mobile phone may be provided in a device with a built-in filter. However, in the case of a device without a display such as a hearing aid, a GUI may be implemented using an external device.

The channel setting unit 600 sets a channel of the digital filter based on the channel setting information of the user. In the equalizer, a channel means an individual pass band of each image or a couplemental image in the digital filter of the present invention, and the channel setting unit 800 sets a channel based on user input information. For example, the user may set the number of channels, and the channel setting unit 600 sets the L value of the filter according to the present invention according to the number of channels set by the user.

For example, when the user sets the number of channels to eight, a total of eight passbands are required. Since four multi-images and a multi-complementary image are required, the image for the multi-image and the multi-complementary image is required. The number L is set to four.

The gain setting unit 602 sets a gain for each pass band (image or complementary image) according to a user's input. When a normalized gain is used, a gain value of 0 to 1 may be set.

The frequency reconstruction unit 606 generates a response of each image in the above-described digital filter and generates a response of all images and complimentary images corresponding to the channel set in the channel setting unit 600. The response of the image and the complementary image can be generated in the same manner as shown in equations (13) and (14).

The equalizer 608 generates a final equalizer output by using the gain value of each frequency band set by the gain setting unit 602 and each image and complimentary response set according to the channel in the frequency reconstructing unit. The equalizer output of which the gain value is adjusted may be expressed as in Equation 15 below.

Although the above has been described with reference to embodiments of the present invention, those skilled in the art may variously modify the present invention without departing from the spirit and scope of the present invention as set forth in the claims below. And can be changed.

Claims (20)

A model filter response storage unit for storing model filter information;
A sampling kernel storage unit applied to the model filter response and scaled by a sampling constant to upsample the model filter response, and generating a multi-image repeated with a predetermined period with respect to the upsampled model filter response;
A complimentary conversion unit for generating a multi-complementary image having the same characteristics as that of the multi-image and repeating the predetermined period in a frequency region in which the multi-image is not generated;
And an image response calculator for calculating a response of the multi-complementary image and an image corresponding to a selected band of the multi-image. The method of claim 1,
If the selected band corresponds to a plurality of multi-image or multi-complementary frequency, further comprising a filter response calculation unit for generating a filter response by summing the responses of each image or the complementary image of the selected band Reconfigurable Digital Filter. The method of claim 1,
And the sampling kernel includes a sampling constant and a multi-image number as variables. The method of claim 3,
The sampling kernel (

) Is a digital filter capable of frequency reconstruction comprising the following equation.

In the above equation, L is a multi-image number and α is a sampling constant. The method of claim 4, wherein
Upsampling a model filter response by applying the sampling kernel and generating a plurality of multi-images is performed by the following equation.

Α is the sampling constant in the above equation,

Is the baseband filter response, L is the image number,

Is the sampling kernel, and the number of multi-images corresponds to the L value. The method of claim 1,
The complimentary converter is configured to generate a multi-image response in a z domain.

Wherein N is the length of the model filter to produce a plurality of multi-complementary images. The method of claim 1,
The image response calculator,
Subtracts the response for generating (L-1) images or the complimentary image from the response for generating the L image or the complementary image for the response operation of the selected L-th image or the complementary image Frequency reconstruction capable of calculating an image response. The method of claim 1,
The repetition period of the multi-image and the multi-complementary image corresponds to a bandwidth of the upsampled model filter response. An upsampling unit configured to perform upsampling to apply a sampling kernel scaled by a sampling constant to a model filter;
A multi-image generator for generating L multi-images that are repeated with a predetermined period with respect to the upsampled model filter response;
A multi-complementary image generator for generating a multi-complementary image having the same characteristics as the multi-image with the predetermined period in a frequency region where the multi-image is not generated; And
And an image response calculator for calculating a response of the multi-complementary image and an image corresponding to a selected band of the multi-image. 10. The method of claim 9,
If the selected band corresponds to a plurality of multi-image or multi-complementary frequency, further comprising a filter response calculation unit for generating a filter response by summing the responses of each image or the complementary image of the selected band Reconfigurable Digital Filter. 10. The method of claim 9,
Upsampling by a sampling kernel scaled by a sampling constant in the sampling kernel is performed by the following equation.

Α is the sampling constant in the above equation,

Is the model filter response,

Is the sampling kernel. 10. The method of claim 9,
And the multi-image generator generates a plurality of multi-images by applying an inverse discrete time fourier transform (IDTFT) to the upsampled model response. The method of claim 12,
And the multi-image generator generates L multi-images in response to the following equation.

Α is the sampling constant in the above equation,

Is the baseband filter response, L is the image number,

Is the sampling kernel, and the number of multi-images corresponds to the L value. 10. The method of claim 9,
The multi-complementary image generator generates a plurality of multi-complementary images by applying an Inverse Discrete Time Fourier Transform (IDTFT) to a complete filter response that delays the upsampled model filter response. Digital filter capable of frequency reconstruction. The method of claim 14,
The multi-complementary image generator generates the upsampled model filter response in a z domain.

Wherein N is the length of the model filter to produce a plurality of multi-complementary images. 16. The method of claim 15,
The multi-complementary image generator is capable of frequency reconstruction, characterized in that for generating the L multi-complementary image in response to the following equation.

In the above equation, c is a factor for indicating the complimentary, α is a sampling constant,

Is the baseband filter response, L is the image number,

Is the sampling kernel, and the number of multi-complementary images corresponds to the L value. 10. The method of claim 9,
The image response calculator,
Subtracts the response for generating (L-1) images or the complimentary image from the response for generating the L image or the complementary image for the response operation of the selected L-th image or the complementary image Frequency reconstruction capable of calculating an image response. 10. The method of claim 9,
The repetition period of the multi-image and the multi-complementary image corresponds to a bandwidth of the upsampled model filter response. A channel setting unit for setting a channel to be used according to the number of channels and channel information selected by the user;
A gain setting unit for setting gain information of each channel;
A frequency reconstruction unit configured to set a response of each channel based on the set number of channels and channel information; And
An equalizer unit is configured to generate an equalizer output by applying the channel gain setting information to the filter response of the frequency reconstruction unit.
The frequency reconstruction unit,
A model filter response storage unit for storing model filter information;
Applied to the model filter response and scaled by a sampling constant to upsample the model filter response, and repeating with a predetermined period for the upsampled model filter response and generating a plurality of multi-images based on the number of channels. Sampling kernel storage,
A complimentary conversion unit for generating a plurality of multi-complementary images based on the number of channels and having the same characteristics as the multi-images, repeated in a frequency region in which the multi-images are not generated;
And an image response calculator for calculating a response of an image corresponding to a selected channel among the multi-complementary image and the multi-image. A channel setting unit for setting a channel to be used according to the number of channels and channel information selected by the user;
A gain setting unit for setting gain information of each channel;
A frequency reconstruction unit configured to set a response of each channel based on the set number of channels and channel information; And
An equalizer unit is configured to generate an equalizer output by applying the channel gain setting information to the filter response of the frequency reconstruction unit.
The frequency reconstruction unit,
An upsampling unit which performs upsampling to apply a sampling kernel scaled by a sampling constant to a model filter;
A multi-image generator for repeating the predetermined sample filter response with a predetermined period and generating L multi-images based on the number of channels;
A multi-complementary image generator for generating L multi-complementary images having the same characteristics as the multi-images in the frequency region where the multi-images are not generated and based on the number of channels;
And an image response calculator for calculating a response of an image corresponding to a selected channel among the multi-complementary image and the multi-image.

Images