[특허]Optimal filtering by neural networks with range extenders and/or reducers

Optimal filtering by neural networks with range extenders and/or reducers 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06F-015/18
출원번호	US-0104488 (1993-08-09)
발명자 / 주소	Lo James Ting-Ho (Ellicott City MD) Yu Lei (Adelphi MD)
출원인 / 주소	Maryland Technology Corporation (Ellicott City MD 02)
인용정보	피인용 횟수 : 57 인용 특허 : 0

초록 ▼

A method and apparatus is provided for processing a measurement process to estimate a signal process, even if the signal and/or measurement processes have large and/or expanding ranges. The method synthesizes training data comprising realizations of the signal and measurement processes into a primary filter for estimating the signal process and, if required, an ancillary filter for providing the primary filter\s estimation error statistics. The primary and ancillary filters each comprise an artificial recurrent neural network (RNN) and at least one range extender or reducer. Their implementation results in the filtering apparatus. Many types of range extender and reducer are disclosed, which have different degrees of effectiveness and computational cost. For a neural filter under design, range extenders and/or reducers are selected from those types jointly with the architecture of the RNN in consideration of the filtering accuracy, the RNN size and the computational cost of each selected range extender and reducer so as to maximize the cost effectiveness of the neural filter. The aforementioned synthesis is performed through training RNNs together with range extenders and/or reducers.

대표청구항 ▼

A method for processing an m-dimensional vector-valued measurement process to estimate an n-dimensional vector-valued signal process, said method comprising the steps of: (1) selecting a recurrent neural network paradigm; (2) selecting an estimation error criterion; (3) generating training data comprising realizations of said signal process and corresponding realizations of said measurement process; (4) constructing a training criterion; (5) selecting at least one range transformer; (6) synthesizing said training data into a primary filter, which comprises a recurrent neural network of said recurrent neural network paradigm and said at least one range transformer; (7) implementing said primary filter; and (8) receiving one measurement vector of said measurement process at a time at at least one input terminal of the implementation of said primary filter and producing an estimate of one signal vector of said signal process at a time at at least one output terminal of the implementation of said primary filter.

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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

Optimal filtering by neural networks with range extenders and/or reducers 원문보기

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Optimal filtering by neural networks with range extenders and/or reducers 원문보기

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이 특허를 인용한 특허 (57)

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