TW197507B - Neural network for performing a relaxation process - Google Patents

Neural network for performing a relaxation process

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Publication number
TW197507B
TW197507B TW81101593A TW81101593A TW197507B TW 197507 B TW197507 B TW 197507B TW 81101593 A TW81101593 A TW 81101593A TW 81101593 A TW81101593 A TW 81101593A TW 197507 B TW197507 B TW 197507B
Authority
TW
Taiwan
Prior art keywords
nodes
output signal
node
objects
class
Prior art date
Application number
TW81101593A
Other languages
Chinese (zh)
Inventor
Shiaw-Shian Yu
Wen-Shyang Tsay
Original Assignee
Ind Tech Res Inst
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ind Tech Res Inst filed Critical Ind Tech Res Inst
Priority to TW81101593A priority Critical patent/TW197507B/en
Application granted granted Critical
Publication of TW197507B publication Critical patent/TW197507B/en

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Abstract

A neural network for implementing a probabilistic relaxation process comprising a plurality of interconnected processing nodes, each node generating an output signal respresenting the time evolution of a probability that a particular object in a set of objects is a member of a particular class in a set of classes, said nodes being interconnected by weighted connection paths such that each node receives a time dependent input signal including a sum of weighted output signals of a plurality of said nodes and an externally generated input signal, the weighting of a connection path connecting two particular nodes being dependent on a compatibility that the corresponding objects of the nodes will be in the corresponding classes of the nodes, each of said processing nodes having a transfer function characteristic so that its output signal is a monotonic non-linear function of its input signal, wherein when the output signal of each node is first set to an initial estimate of the probability that a particular object in a set of objects is a member of a particular class in a set of class, said output signal of each node evolves over time due to the interconnection between said nodes to a constant final value indicative of whether or not a particular object is in a particular class.
TW81101593A 1992-02-29 1992-02-29 Neural network for performing a relaxation process TW197507B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
TW81101593A TW197507B (en) 1992-02-29 1992-02-29 Neural network for performing a relaxation process

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
TW81101593A TW197507B (en) 1992-02-29 1992-02-29 Neural network for performing a relaxation process

Publications (1)

Publication Number Publication Date
TW197507B true TW197507B (en) 1993-01-01

Family

ID=51356406

Family Applications (1)

Application Number Title Priority Date Filing Date
TW81101593A TW197507B (en) 1992-02-29 1992-02-29 Neural network for performing a relaxation process

Country Status (1)

Country Link
TW (1) TW197507B (en)

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