Electronic neural net algorithm for maximum entropy solutions to ill-posed problems. II. Multiply connected electronic circuit implementation

For pt.I see ibid., vol.36, no.2, p.288-94 (1989). Using standard electronic components, the authors have constructed a multiply connected analog circuit that minimizes a specific cost function of its external inputs, interconnects, and node characteristics. The circuit is designed so that the cost...

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Published inIEEE transactions on circuits and systems Vol. 37; no. 1; pp. 110 - 113
Main Authors Marrian, C.R.K., Mack, I.A., Banks, C., Peckerar, M.C.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.01.1990
Institute of Electrical and Electronics Engineers
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ISSN0098-4094
DOI10.1109/31.45695

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Abstract For pt.I see ibid., vol.36, no.2, p.288-94 (1989). Using standard electronic components, the authors have constructed a multiply connected analog circuit that minimizes a specific cost function of its external inputs, interconnects, and node characteristics. The circuit is designed so that the cost function contains an informational entropy regularizer to give maximum-entropy solutions to ill-posed problems. The circuit performs a gradient search to achieve the minimization in a time defined by a circuit RC time constant rather than the complexity of the problem. The circuit reaches a stable equilibrium condition irrespective of the initial values of its outputs. For the circuit considered, once a partial compensation was made for the input offset voltages of the operational amplifiers used, the solution generated by the circuit was close to the 0.1% estimated for an ideal circuit. Settling times of about 15 ms were observed. The nature of the particular problem chosen required extremely high gains on the constraint nodes in the circuit. The resulting stability problems were overcome by slowing the response of the signal nodes in the circuit.< >
AbstractList For pt.I see ibid., vol.36, no.2, p.288-94 (1989). Using standard electronic components, the authors have constructed a multiply connected analog circuit that minimizes a specific cost function of its external inputs, interconnects, and node characteristics. The circuit is designed so that the cost function contains an informational entropy regularizer to give maximum-entropy solutions to ill-posed problems. The circuit performs a gradient search to achieve the minimization in a time defined by a circuit RC time constant rather than the complexity of the problem. The circuit reaches a stable equilibrium condition irrespective of the initial values of its outputs. For the circuit considered, once a partial compensation was made for the input offset voltages of the operational amplifiers used, the solution generated by the circuit was close to the 0.1% estimated for an ideal circuit. Settling times of about 15 ms were observed. The nature of the particular problem chosen required extremely high gains on the constraint nodes in the circuit. The resulting stability problems were overcome by slowing the response of the signal nodes in the circuit.< >
Author Peckerar, M.C.
Marrian, C.R.K.
Mack, I.A.
Banks, C.
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10.1038/272686a0
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Keywords Method of maximum entropy
Neural network
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Lyapunov function
Information theory
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Snippet For pt.I see ibid., vol.36, no.2, p.288-94 (1989). Using standard electronic components, the authors have constructed a multiply connected analog circuit that...
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StartPage 110
SubjectTerms Analog circuits
Applied sciences
Circuit properties
Circuit stability
Cost function
Electric, optical and optoelectronic circuits
Electronic circuits
Electronic components
Electronics
Entropy
Exact sciences and technology
Integrated circuit interconnections
Minimization
Miscellaneous
Neural networks
Operational amplifiers
Voltage
Title Electronic neural net algorithm for maximum entropy solutions to ill-posed problems. II. Multiply connected electronic circuit implementation
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