Add to ORKGMöller R, Maris M, Tomes J, Mojaev A. A strong winner-take-all neural network in analogue hardware. In: Smith LS, Hamilton A, eds. Neuromorphic Systems: Engineering Silicon from Neurobiology. World Scientific; 1998: 178-190
The neural computation field had finally delivered on its promises in 2013 when the University of To...
This paper describes a complete silicon implementation of an Artificial Neural Network based on Cohe...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
Abstract. We describe an aVLSI network consisting of a group of excitatory neurons and a global inhi...
Abstract. We describe an aVLSI network consisting of a group of excitatory neurons and a global inhi...
Abstract—A subthreshold MOS integrated circuit (IC) is de-signed and fabricated for implementing a c...
Neural systems found in the brains of even very simple animals are amazingly effective at performing...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
An analog MOS circuit is proposed for implementing a Lotka–Volterra (LV) competitive neural network ...
Indiveri G, Chicca E, Douglas RJ. Artificial cognitive systems: From VLSI networks of spiking neuron...
The explosive growth of data and information has motivated technological developments in computing s...
We have designed, fabricated, and tested a series of compact CMOS integrated circuits that realize t...
Neuromorphic Very Large Scale Integration (VLSI) devices emulate the activation dynamics of biologic...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
Neuromorphic systems emulate the organization and function of nervous systems. They are usually comp...
The neural computation field had finally delivered on its promises in 2013 when the University of To...
This paper describes a complete silicon implementation of an Artificial Neural Network based on Cohe...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
Abstract. We describe an aVLSI network consisting of a group of excitatory neurons and a global inhi...
Abstract. We describe an aVLSI network consisting of a group of excitatory neurons and a global inhi...
Abstract—A subthreshold MOS integrated circuit (IC) is de-signed and fabricated for implementing a c...
Neural systems found in the brains of even very simple animals are amazingly effective at performing...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
An analog MOS circuit is proposed for implementing a Lotka–Volterra (LV) competitive neural network ...
Indiveri G, Chicca E, Douglas RJ. Artificial cognitive systems: From VLSI networks of spiking neuron...
The explosive growth of data and information has motivated technological developments in computing s...
We have designed, fabricated, and tested a series of compact CMOS integrated circuits that realize t...
Neuromorphic Very Large Scale Integration (VLSI) devices emulate the activation dynamics of biologic...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
Neuromorphic systems emulate the organization and function of nervous systems. They are usually comp...
The neural computation field had finally delivered on its promises in 2013 when the University of To...
This paper describes a complete silicon implementation of an Artificial Neural Network based on Cohe...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...