CN113390464A - Resistance-variable sensing framework for coded pulse output - Google Patents

Resistance-variable sensing framework for coded pulse output Download PDF

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CN113390464A
CN113390464A CN202110714948.3A CN202110714948A CN113390464A CN 113390464 A CN113390464 A CN 113390464A CN 202110714948 A CN202110714948 A CN 202110714948A CN 113390464 A CN113390464 A CN 113390464A
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memristor
mit
resistive
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resistance
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CN113390464B (en
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韩传余
方胜利
韩峥嵘
张骐智
刘卫华
李昕
王小力
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Xian Jiaotong University
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    • G06N3/049—Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
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Abstract

The invention discloses a resistance change type sensing framework for coded pulse output, which comprises a coded pulse output unit and a frequency calculation unit, wherein the coded pulse output unit comprises a resistance change type sensor and an MIT (MIT) memristor; the frequency calculation unit comprises a voltage comparator and an MCU module; the voltage source is connected with one end of the MIT memristor and the input end of the voltage comparator through the resistance variation type sensor, the other end of the MIT memristor is grounded, the output end of the voltage comparator is connected with the input end of the MCU module, and the framework can effectively solve the problems of complex system hardware structure, large power consumption, large data transmission quantity and low efficiency.

Description

Resistance-variable sensing framework for coded pulse output
Technical Field
The invention belongs to the field of intelligent sensing, neural networks and brain-like computing, and relates to a resistive deformation type sensing framework for coded pulse output.
Background
Intelligent systems based on artificial neural networks have been the core driver of the information technology revolution. At present, artificial intelligence systems have been widely used in manufacturing, home, finance, retail, transportation, security, medical, logistics, education, and other industries. The impulse neural network as a third generation neural network model can simulate the information coding and processing process of the human brain, and realizes a higher biological nerve simulation level. The pulse neural network processes the biological-like pulse signals, the common sensor outputs analog electric signals, and the communication between the two signals needs a relatively complex conversion circuit, so that the problems of complex system hardware structure, high power consumption, large data transmission quantity and low efficiency are often caused.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a resistive switching type sensing framework for coded pulse output, which can effectively solve the problems of complex system hardware structure, high power consumption, large data transmission quantity and low efficiency.
In order to achieve the purpose, the resistance variation type sensing framework for outputting the coding pulse comprises a coding pulse output unit and a frequency calculation unit, wherein the coding pulse output unit comprises a resistance variation type sensor and an MIT memristor; the frequency calculation unit comprises a voltage comparator and an MCU module;
the voltage source is connected with one end of the MIT memristor and the input end of the voltage comparator through the resistance variation type sensor, the other end of the MIT memristor is grounded, and the output end of the voltage comparator is connected with the input end of the MCU module.
Also included is a fixed capacitance connected in parallel with the MIT memristor.
When the voltage across the MIT memristor reaches its threshold voltage VthWhen the MIT memristor is in a high resistance state, the resistance value of the MIT memristor is changed into a low resistance state; when the two-terminal voltage of the MIT memristor is reduced to the holding voltage V thereofholdWhen the MIT memristor is in the high-resistance state, the resistance value of the MIT memristor is changed from low resistance to high resistance.
By connecting a fixed capacitor in parallel across the MIT memristor or using its own parasitic capacitance, a voltage pulse signal is output across the MIT memristor.
When different constant currents are input to charge the fixed capacitor, a stable voltage pulse signal is generated across the MIT memristor, and the frequency of the output voltage pulse signal increases as the input current increases.
External stimuli are sensed by the resistive strain type sensor.
The resistance change type sensor is a resistance change type pressure sensor, a resistance change type gas sensor, a resistance change type temperature sensor, a resistance change type humidity sensor or a resistance change type photosensitive sensor.
The MIT memristor is a vanadium oxide-based MOTT type metal insulator transition memristor or a niobium oxide-based MOTT type metal insulator transition memristor.
The invention has the following beneficial effects:
when the resistance variable type sensing framework of the coded pulse output is in specific operation, when the external environment changes, the resistance value of the resistance variable type sensor changes, meanwhile, under the condition of constant input voltage, the input current can correspondingly change, and when the input current changes, the frequency of the output voltage pulse correspondingly changes, so that a sensing signal is directly converted into a voltage pulse signal V with different frequenciesout1A voltage pulse signal V to be outputout1Is input to a voltage comparator to generate square wave pulse signals V with corresponding frequencyout2And then the signal is input into the MCU module to calculate the pulse frequency in real time, so that the signal sensed by the sensor is directly converted into a pulse signal through a simple circuit structure, the key problem of difficult communication between the sensor and a pulse neural network at present is solved, and the problems of complex system hardware structure, large power consumption, large data transmission quantity and low efficiency are solved.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 shows an MIT memristor R based on vanadium oxide or niobium oxideMIV graph of (d);
FIG. 3a shows a constant current of 120uA at the input, with the addition of a fixed capacitance C of 10uFFA schematic diagram of a voltage pulse signal generated in the case of (1);
FIG. 3b shows a constant input current at 120uA without an external fixed capacitor CFA schematic diagram of a voltage pulse signal generated in the case of (1);
fig. 4 is a graph of the relationship between input current magnitude and output frequency.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments, and are not intended to limit the scope of the present disclosure. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
There is shown in the drawings a schematic block diagram of a disclosed embodiment in accordance with the invention. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.
Referring to fig. 1, the resistive switching type sensing architecture for coded pulse output according to the present invention includes a coded pulse output unit and a frequency calculation unit;
the coded pulse output unit comprises a resistive type sensor RSAnd a fixed capacitor CFAnd MIT memristor RM(ii) a The frequency calculation unit comprises a voltage comparator D and an MCU module;
voltage source transresistance type sensor RSAnd a fixed capacitor CFOne terminal of (1), MIT memristor RMIs connected to the input of the voltage comparator D, MIT memristor RMAnother terminal of (1) and a fixed capacitor CFThe other end of the voltage comparator D is grounded, and the output end of the voltage comparator D is connected with the input end of the MCU module.
Resistive switching type sensor RSThe sensor is a resistance-change type pressure sensor, a resistance-change type gas sensor, a resistance-change type temperature sensor, a resistance-change type humidity sensor or a resistance-change type photosensitive sensor; MIT memristor RMThe metal-insulator transition memristor is a vanadium oxide-based MOTT type metal-insulator transition memristor or a niobium oxide-based MOTT type metal-insulator transition memristor.
The working principle of the invention is as follows:
MIT memristor RMIV characteristics of (1) when MIT memristor R is shown in FIG. 2MThe voltage across reaches its threshold voltage VthWhile, MIT memristor RMThe resistance value of (2) is changed from high resistance to low resistance; when MIT memristor RMTo its holding voltage VholdWhile, MIT memristor RMChanges from low resistance to high resistance, reciprocates thereby to memristor R at MITMThe voltage pulse signals are outputted from both ends, as shown in FIG. 3a and FIG. 3b, when using the external fixed capacitor CFOr when the parasitic capacitance of the MIT memristor is used, the resistance can be obtained at the MIT memristor RMA stable voltage pulse signal is generated across the terminals and the frequency of the output voltage pulse signal increases with increasing input current, as shown in fig. 4.
Resistive switching type sensor RSFor sensing external stimuli such as temperature, light intensity, humidity, gas concentration, gas type and pressure signal. Taking gas concentration as an example, when the concentration of the external gas changes, the resistance change type gas sensor RSWhile the input current changes correspondingly under the condition of constant input voltage, as shown in fig. 4, when the input current changes, the frequency of the output voltage pulse changes correspondingly, so that the gas signal is directly converted into different frequenciesVoltage pulse signal of (2).
The output voltage pulse signal Vout1Is input to a voltage comparator D to generate a square wave pulse signal V of corresponding frequencyout2And then input into the MCU module to calculate the pulse frequency in real time.

Claims (8)

1. The resistive deformation type sensing framework for outputting the coded pulse is characterized by comprising a coded pulse output unit and a frequency calculation unit, wherein the coded pulse output unit comprises a resistive deformation type sensor (R)S) And MIT memristor (R)M) (ii) a The frequency calculation unit comprises a voltage comparator (D) and an MCU module;
voltage source sensor (R) via resistive changeS) And MIT memristor (R)M) Is connected to the input of a voltage comparator (D), and an MIT memristor (R)M) The other end of the voltage comparator (D) is grounded, and the output end of the voltage comparator (D) is connected with the input end of the MCU module.
2. The resistive-switching type sensing architecture of coded pulse output according to claim 1, further comprising a MIT memristor (R) andM) Parallel connected fixed capacitors (C)F)。
3. Resistive-type sensing architecture for coded pulse output according to claim 1, characterized when MIT memristor (R)M) The voltage across reaches its threshold voltage VthMIT memristor (R)M) The resistance value of (2) is changed from high resistance to low resistance; when MIT memristor (R)M) To its holding voltage VholdMIT memristor (R)M) The resistance value of (2) is changed from low resistance to high resistance.
4. Resistive-type sensing architecture for encoding pulsed output according to claim 2, characterized by passing through at MIT memristor (R)M) Fixed capacitor C with two parallel endsFOr utilize its own parasitic capacitance to memristor (R) at MITM) The two ends output voltage pulse signals.
5. The resistive-switching sensing architecture of claim 2, wherein the fixed capacitance C is applied when different constant currents are appliedFOn charging, at MIT memristor (R)M) The two ends generate stable voltage pulse signals, and the frequency of the output voltage pulse signals is increased along with the increase of the input current.
6. Resistive-type sensing architecture for coded pulse output according to claim 1, characterized by the fact that it passes through a resistive-type sensor (R)S) And (5) feeling external stimuli.
7. Resistive-type sensing architecture for coded pulse output according to claim 6, characterized by resistive-type sensors (R)S) Is a resistance change type pressure sensor, a resistance change type gas sensor, a resistance change type temperature sensor, a resistance change type humidity sensor or a resistance change type photosensitive sensor.
8. Resistive-type sensing architecture of coded pulse output according to claim 1, characterized by MIT memristor (R)M) The metal-insulator transition memristor is a vanadium oxide-based MOTT type metal-insulator transition memristor or a niobium oxide-based MOTT type metal-insulator transition memristor.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114440942A (en) * 2022-02-17 2022-05-06 陕西格芯国微半导体科技有限公司 Novel sensor of perception coding integration based on mott memristor

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EP3168577A1 (en) * 2015-11-13 2017-05-17 Nokia Technologies Oy A multifunctional sensor apparatus and associated methods
CN206974564U (en) * 2017-03-15 2018-02-06 广州视源电子科技股份有限公司 Thermistor temperature detection device and air conditioner
CN109510616A (en) * 2018-12-12 2019-03-22 中国科学技术大学 Sensor interface control circuit based on RC oscillating circuit
CN110345981A (en) * 2019-07-29 2019-10-18 中国科学技术大学 The detection system of resistance sensor
CN111585562A (en) * 2020-04-29 2020-08-25 西安交通大学 Capacitive touch sensing unit for nerve morphology output
CN111585563A (en) * 2020-04-29 2020-08-25 西安交通大学 Piezoresistive tactile sensing unit for nerve form output
CN111753976A (en) * 2020-07-02 2020-10-09 西安交通大学 Electronic afferent neuron for neuromorphic impulse neural network and implementation method

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Publication number Priority date Publication date Assignee Title
EP3168577A1 (en) * 2015-11-13 2017-05-17 Nokia Technologies Oy A multifunctional sensor apparatus and associated methods
CN206974564U (en) * 2017-03-15 2018-02-06 广州视源电子科技股份有限公司 Thermistor temperature detection device and air conditioner
CN109510616A (en) * 2018-12-12 2019-03-22 中国科学技术大学 Sensor interface control circuit based on RC oscillating circuit
CN110345981A (en) * 2019-07-29 2019-10-18 中国科学技术大学 The detection system of resistance sensor
CN111585562A (en) * 2020-04-29 2020-08-25 西安交通大学 Capacitive touch sensing unit for nerve morphology output
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CN111753976A (en) * 2020-07-02 2020-10-09 西安交通大学 Electronic afferent neuron for neuromorphic impulse neural network and implementation method

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114440942A (en) * 2022-02-17 2022-05-06 陕西格芯国微半导体科技有限公司 Novel sensor of perception coding integration based on mott memristor

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