Add to ORKGA new CMOS architecture for Hopfield's neural networks is proposed. The use of differential amplifiers and active synapses allows the implementation of hundreds of neurons on a single chip. Since it is fully programmable, the circuit can be used as a content-addressable memory as well as in optimization problems
Future development of neural networks and their applications will be strongly affected by the availa...
<p>In recent years, neuromorphic architectures have been an increasingly effective tool used to solv...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...
Abstrud-Hopfield’s neural networks show retrieval and speed capabili-ties that make them good candid...
Neural networks used as content-addressable memories show unequaled retrieval and speed capabilities...
I present an abstraction of the Hopfield-model for neural networks which is suitable for physical ch...
Simple nonlinear synapse circuit proposes fo r implementation of artificial neural networks using st...
The electrophysiological behavior of real neurons is emulated by the silicon neuron. The network of ...
A large scale collective system implementing a specific model for associative memory was described b...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
The recent resurgence of interest in neural networks (NNs) has resulted in the application of NNs t...
Artificial neural networks are systems composed of interconnected simple computing units known as a...
International audienceEncoded neural networks mix the principles of associative memories and error-c...
In contrast with analog design, digital design and implementation of any logic circuit suffer much f...
Future development of neural networks and their applications will be strongly affected by the availa...
<p>In recent years, neuromorphic architectures have been an increasingly effective tool used to solv...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...
Abstrud-Hopfield’s neural networks show retrieval and speed capabili-ties that make them good candid...
Neural networks used as content-addressable memories show unequaled retrieval and speed capabilities...
I present an abstraction of the Hopfield-model for neural networks which is suitable for physical ch...
Simple nonlinear synapse circuit proposes fo r implementation of artificial neural networks using st...
The electrophysiological behavior of real neurons is emulated by the silicon neuron. The network of ...
A large scale collective system implementing a specific model for associative memory was described b...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
The recent resurgence of interest in neural networks (NNs) has resulted in the application of NNs t...
Artificial neural networks are systems composed of interconnected simple computing units known as a...
International audienceEncoded neural networks mix the principles of associative memories and error-c...
In contrast with analog design, digital design and implementation of any logic circuit suffer much f...
Future development of neural networks and their applications will be strongly affected by the availa...
<p>In recent years, neuromorphic architectures have been an increasingly effective tool used to solv...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...