[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Yang et al., 1990 - Google Patents

VLSI implementation of cellular neural networks

Yang et al., 1990

View PDF
Document ID
4583331022639108153
Author
Yang L
Chua L
Krieg K
Publication year
Publication venue
IEEE international symposium on circuits and systems

External Links

Snippet

A cellular neural network (CNN) which is an example of very-large-scale analog processing or collective analog computation is presented. The CNN architecture combines some features of fully connected analog neural networks with the nearest-neighbor interactions …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/0635Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • G06N3/082Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation

Similar Documents

Publication Publication Date Title
Yang et al. VLSI implementation of cellular neural networks
Graf et al. VLSI implementation of a neural network memory with several hundreds of neurons
Montalvo et al. Toward a general-purpose analog VLSI neural network with on-chip learning
Basu et al. Neural dynamics in reconfigurable silicon
Van der Spiegel et al. An analog neural computer with modular architecture for real-time dynamic computations
Foo et al. Analog components for the VLSI of neural networks
Linares-Barranco et al. A CMOS analog adaptive BAM with on-chip learning and weight refreshing
Milev et al. Analog implementation of ANN with inherent quadratic nonlinearity of the synapses
Hsu et al. Competitive learning with floating-gate circuits
Weinfeld A fully digital integrated CMOS Hopfield network including the learning algorithm
Lee et al. Paralleled hardware annealing for optimal solutions on electronic neural networks
Anguita et al. Analog CMOS implementation of a discrete time CNN with programmable cloning templates
JPH0277871A (en) Neural network
Caviglia et al. Effects of weight discretization on the back propagation learning method: Algorithm design and hardware realization
Krieg et al. Analog signal processing using cellular neural networks
Serrano-Gotarredona et al. A real-time clustering microchip neural engine
Chou et al. VLSI design of optimization and image processing cellular neural networks
Serrano-Gotarrdeona et al. An ART1 microchip and its use in multi-ART1 systems
Murray et al. Fully-programmable analogue VLSI devices for the implementation of neural networks
Furman et al. An analog CMOS backward error-propagation LSI
Nowshin et al. Energy efficient and adaptive analog ic design for delay-based reservoir computing
Anguita et al. A low-power CMOS implementation of programmable CNN's with embedded photosensors
Card et al. Learning capacitive weights in analog CMOS neural networks
Carmona et al. CMOS realization of a 2-layer CNN universal machine chip
Basu et al. Bifurcations in a silicon neuron