Data processing: artificial intelligence – Neural network – Structure
Reexamination Certificate
2007-10-09
2007-10-09
Hirl, Joseph P (Department: 2129)
Data processing: artificial intelligence
Neural network
Structure
C706S015000, C706S026000
Reexamination Certificate
active
09771019
ABSTRACT:
A neural network computer (20) includes a weighting network (21) coupled to a plurality of phase-locked loop circuits (251-25N). The weighting network (21) has a plurality of weighting circuits (C11, . . . , CNN) having output terminals connected to a plurality of adder circuits (311-31N). A single weighting element (Ckj) typically has a plurality of output terminals coupled to a corresponding adder circuit (31k). Each adder circuit (31k) is coupled to a corresponding bandpass filter circuit (31k) which is in turn coupled to a corresponding phase-locked loop circuit (25k). The weighting elements (C1,1, . . . , CN,N) are programmed with connection strengths, wherein the connection strengths have phase-encoded weights. The phase relationships are used to recognize an incoming pattern.
REFERENCES:
patent: 4815475 (1989-03-01), Burger
patent: 5072130 (1991-12-01), Dobson
patent: 5263122 (1993-11-01), Nunally
patent: 5446828 (1995-08-01), Woodall
patent: 5479577 (1995-12-01), Yang
patent: 5705956 (1998-01-01), Neely
patent: 6581046 (2003-06-01), Ahissar
patent: PCS/US99/26698 (1999-11-01), None
Hiroaki Kurokawa, A Local Connected Neural Oscillator Network for Sequential Character Segmentation, Jun. 1997, IEEE, 0-7803-4122-8/97, 838-843.
Hiroaki Kurokawa et al, The Stability of the Synchronization Learning of the Oscillatory Neural Networks, 1997, IEEE, 0-7803-3583-X/97, 513-516.
Murphy et al, A Novel Learning Algorithm for Global Synchronization of Oscillatory Neural Networks, 1999, IEEE, 0-7803-5471-0/99, V-551-V-554.
Liu & Chiang,Phase-locked Loop with neurocontroller.
Wang,An Oscillation Model of Auditory Stream Segregation.
Kaburlasos; Egberg & Tacker,Self Adaptive Multidimensional Euclidean Neural Networks for Pattern Recognition.
Lane; Handelman & Gelfand,Development of Adaptive B-Splines Using CMAC Neural Networks.
Kuesewski; Myers & Steck,Adaptive Modelling for Cognitive Structures.
Lange; Videl & Dyer,Phase-Locking of Artificial Neural Oscillators can Perform Dynamic Role-Binding and Inferencing.
Endo & Kinouchi,Neural Network with Interacting Oscillators to Generate Low Frequency Rhythm.
Buhmann & von der Malsburg,Sensory Segmentation by Neural Oscillators.
Kurokawa; Ho & Mori,A Local Connected Neural Oscillator Network for Sequential Character Segmentation.
Hoppenstead & Izhikevich;Optical Computation via Phase Modulation of Laser Oscillators.
F. C. Hoppensteadt, E. Izhikevich, “Canonical Models for Bifurcations from Equilibrium in Weakly Connected Neural Networks,” WCNN'95, Washington, D.C., vol. 1, pp. 180-183.
F. C. Hoppensteadt, E. M. Izhikevich, “Synaptic Organizations and Dynamical Properties of Weakly Connected Neural Oscillators,” Biol. Cybern. 75, 117-127 (1996).
F. C. Hoppensteadt, E. M. Izhikevich, “Synaptic Organizations and Dynamical Properties of Weakly Connected Neural Oscillators,” Biol. Cybern. 75, 129-135 (1996).
E. Ahissar, “Temporal-Code to Rate-Code Conversion by Neuronal Phase-Locked Loops,” Neural Computaion 10, 597-650 (1998).
Hoppensteadt Frank C.
Izhikevich Eugene M.
Arizona Board of Regents
Hirl Joseph P
Schwabe Williamson & Wyatt P.C.
LandOfFree
Phase-locked loop oscillatory neurocomputer does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Phase-locked loop oscillatory neurocomputer, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Phase-locked loop oscillatory neurocomputer will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3831038