[특허]Method for training a neural network for classifying an unknown signal with respect to known signals

Method for training a neural network for classifying an unknown signal with respect to known signals 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06F-015/18
출원번호	US-0904734 (1992-06-25)
우선권정보	FR-0008066 (1991-06-28)
발명자 / 주소	Minot Jol (Charenton FRX) Gentric Philippe (Paris FRX)
출원인 / 주소	U.S. Philips Corporation (New York NY 02)
인용정보	피인용 횟수 : 27 인용 특허 : 0

초록 ▼

The device includes a neural network with an input layer 3, an internal layer 4, and an output layer 5. This network is designed to classify data vectors to classes, the synaptic weights in the network being determined through programming on the basis of specimens whose classes are known. Each class is defined during programming as corresponding to a set of neurons of which each represents a domain which contains a fixed number of specimens. The network includes a number of neurons and synaptic weights which have been determined as a function of the classes thus defined.

대표청구항 ▼

A method for training a neural network to classify an unknown signal of a known type, comprising the steps of: a) selecting at least one feature from each of a plurality of known signals having at least one feature; b) determining a difference between the selected at least one feature for every different pair of known signals wherein the differences are represented by a plurality of difference-vectors; c) selecting a first one of the differences vectors as a current difference-vector and determining the k nearest difference-vectors from said current difference-vector wherein a decision domain is created including a group of k+1 difference-vectors; d) calculating a distribution probability for the group of difference-vectors in the decision domain; e) introducing a neuron corresponding to the decision domain into an internal layer of neurons of the neural network; f) calculating a weight represented by aij and a weight represented by bi for each difference-vector connection between an input layer of neurons and the internal layer based upon the distribution probability of the decision domain; and g) selecting a next one of the difference-vectors as a new current difference-vector and repeating steps (c) through (g) until the last difference-vector is processed, and h) inputting a plurality of unknown signal difference-vectors into an input layer of the network and calculating a probability based upon the weighting coefficients aij and bi that the unknown signal difference-vectors lie within one of the decision domains, whereby the neural network is trained to classify the differences between the unknown signal and the known signals thus indicating the degree of correspondence between the unknown signal and the known signals.

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IPC	Description
A	생활필수품
A62	인명구조; 소방(사다리 E06C)
A62B	인명구조용의 기구, 장치 또는 방법(특히 의료용에 사용되는 밸브 A61M 39/00; 특히 물에서 쓰이는 인명구조 장치 또는 방법 B63C 9/00; 잠수장비 B63C 11/00; 특히 항공기에 쓰는 것, 예. 낙하산, 투출좌석 B64D; 특히 광산에서 쓰이는 구조장치 E21F 11/00)
A62B-1/08	.. 윈치 또는 풀리에 제동기구가 있는 것

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연합인증

Method for training a neural network for classifying an unknown signal with respect to known signals 원문보기

초록 ▼

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Method for training a neural network for classifying an unknown signal with respect to known signals 원문보기

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연구과제 타임라인

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이 특허를 인용한 특허 (27)

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