Patent EP0294116A2 successfully refreshed from Google Patents.
EP0294116A2
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EP
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Digital adaptive receiver employing maximum-likelihood sequence estimation with neural networks
Assignee: Texas Instruments Inc
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Filing: 1988-05-27
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Granted: —
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Expires: 2008-05-27
Abstract
Abstract A maximum-likelihood sequence estimator receiver includes a matched filter (56) connected to a digital transmission channel (58) and a sampler (60) for providing sampled signals output by the matched filter (56). The sampled signals are input to an analog neural network (68) to provide high-speed outputs representative of the transmission channel signals. The neural network outputs (70) are also provided as inputs to a coefficient esitmator (78) which produces coefficients for feedback to the matched filter (56). For time-varying transmission channel characteristics, the coefficient estimator (78) provides a second coefficient output which is utilized for changing the interconnection strenghts of the neural network connection matrix to offset the varying transmission channel characteristics.
Inventors
- 👤 John D. Provence
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-10-29 14:41
CPC Classifications
H; H04; H04L; H04L25/00; H04L25/02; H04L25/03; H04L25/03006; H04L25/03165; G; G06; G06J; G06J1/00; G06J1/005; G06N; G06N3/00; G06N3/02; G06N3/04; G06N3/044; G06N3/08; G06N3/082; G06N3/09; H04L2025/03433; H04L2025/03439; H04L2025/03445; H04L2025/03464
Claims Analysis
Total Claims: 14
Claim 1
Independent Claim
63 words
A digital receiver for maximum-likelihood sequence estimation of digital signals transmitted over a time-dispersive transmission channel, comprising: a matched filter with an input for receiving signals transmitted over the transmission channel; and a neural network for receiving sampled signals output by said matched filter and for providing output signals of said receiver which are estimates of signals initially transmitted over said transmission channel.
Claim 2
Dependent Claim
63 words
A digital receiver for maximum-likelihood sequence estimation of digital signals transmitted over a time-dispersive transmission channel, comprising: a matched filter with an input for receiving signals transmitted over the transmission channel; and a neural network for receiving sampled signals output by said matched filter and for providing output signals of said receiver which are estimates of signals initially transmitted over said transmission channel.
Claim 3
Dependent Claim
40 words
The receiver of Claim 1 further including a coefficient estimator for receiving digital signals output by said neural network and for producing coefficient information for input back to said neutral network to modify feedback connection strengths of said neural network.
Claim 4
Dependent Claim
20 words
The receiver of Claim 1 wherein said neural network comprises an analog circuit having a number of high gain amplifiers.
Claim 5
Dependent Claim
37 words
The receiver of Claim 1 wherein said neural network includes M inputs, and further including an N-bit storage register for storing digital information output by said matched filter for input to respective inputs of said neural network.
Claim 6
Dependent Claim
33 words
The receiver of Claim I further including a switch connected to the input of said natural network for momentarily switching said input to a reference to precondition said neural network to predefined states.
Claim 7
Dependent Claim
49 words
The receiver of Claim 2 further including a thresholding device connected between the output of said neural network and said coefficient estimator, said thresholding device being operation to produce as an output thereof a first state or a second state from an analog signal output by said neural network.
Claim 8
Dependent Claim
38 words
The receiver of Claim 2 further including a logic circuit connected to the output of said coefficient estimator and to said neutral network for providing changes in interconnection strengths within said neural network for time varying channel characteristics.
Claim 9
Dependent Claim
25 words
The receiver of Claim 2 further including a sampler for sampling signals carried by said channel and inputting said sampled signals to said coefficient estimator.
Claim 10
Independent Claim
63 words
A method of processing signals received over a digital transmission channel using maximum-likelihood sequence estimation techniques, comprising the steps of: coupling the signals through a filter adapter for matching to the transmission channel; converting the signals to digital signals; and presenting the digital signals to a neural network to provide a high-speed output estimation of the signals initially transmitted of the transmission channel.
Claim 11
Independent Claim
63 words
A method of processing signals received over a digital transmission channel using maximum-likelihood sequence estimation techniques, comprising the steps of: coupling the signals through a filter adapter for matching to the transmission channel; converting the signals to digital signals; and presenting the digital signals to a neural network to provide a high-speed output estimation of the signals initially transmitted of the transmission channel.
Claim 12
Dependent Claim
34 words
The method of Claim 28 further including producing feedback coefficients using the output of said neural network; and coupling the coefficients back to said neural network for changing connection strengths in said neural network.
Claim 13
Dependent Claim
38 words
The method of Claim 28 further including coupling the digital signals to said neural network in groups of said digital signals, wherein ones of said digital signals in each said group are common and thus overlapped in time.
Claim 14
Dependent Claim
53 words
The method of Claim 9 further including providing said neural network with a connection matrix for interconnecting neurons of said neural network with desired strengths, and changing the strengths of said connection matrix when predetermined electrical characteristics of said transmission channel change to thereby provide an adaptive receiver for time varying transmission channels.
References Cited (Backward Citations)
No citation records indexed.
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