[특허]Self-organizing pattern classification neural network system

Self-organizing pattern classification neural network system 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06K-009/62
출원번호	US-0832678 (1992-02-06)
발명자 / 주소	Yoda Fumio (Hillsboro OR)
출원인 / 주소	Mitsubishi Denki Kabushiki Kaisha (JPX 03)
인용정보	피인용 횟수 : 56 인용 특허 : 0

초록 ▼

A self-organizing pattern classification neural network system includes means for receiving incoming pattern of signals that were processed by feature extractors that extract feature vectors from the incoming signal. These feature vectors correspond to information regarding certain features of the incoming signal. The extracted feature vectors then each pass to separate self-organizing neural network classifiers. The classifiers compare the feature vectors to templates corresponding to respective classes and output the results of their comparisons. The output from the classifier for each class enter a discriminator. The discriminator generates a classification response indicating the best class for the input signal. The classification response includes information indicative of whether the classification is possible and also includes the identified best class. Lastly, the system includes a learning trigger for transferring a correct glass signal to the self-organizing classifiers so that they can determine the validity of their classification results.

대표청구항 ▼

A self-organizing pattern classification neural network system for classifying incoming pattern signals into their classes, comprising: (a) feature extractors for extracting different feature vectors from an incoming pattern signal; (b) self-organizing neural network classifiers, one for each of said features extractors, for receiving the feature vectors and generating response vectors, each response vector comprising a plurality of response scalars corresponding to the respective classes wherein each said self-organizing classifier comprises: i) input nodes for receiving feature scalars of each of said feature vectors; ii) a plurality of intermediate nodes for receiving said feature scalars for said input nodes and for generating a plurality of intermediate outputs; iii) a plurality of output nodes for receiving intermediate outputs of intermediate nodes of a class, for determining a smallest intermediate output, and for transferring, to said discriminator, said smallest intermediate output as a response scalar; iv) a self-organizing selector for receiving said smallest intermediate output and a node number of said intermediate node which gives said smallest intermediate output and for determining a weights update signal based on node number and said intermediate output from said intermediate node, and a correct class signal from said learning trigger; and c) a discriminator for receiving said response vectors and generating a classification response, which includes information indicative of whether classification is possible and also includes an identified class; and d) a learning trigger for transferring a correct class signal to said self-organizing classifiers based on a class of said incoming pattern signal and based on said classification response.

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A62B-1/08	.. 윈치 또는 풀리에 제동기구가 있는 것

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연합인증

Self-organizing pattern classification neural network system 원문보기

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Self-organizing pattern classification neural network system 원문보기

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