Results from working analog VLSI implementations of two different pulse stream neural network forms are reported. The circuits are rendered relatively invariant to processing variations, and the problem of cascadability of synapses to form large systems is addressed. A strategy for interchip communication of large numbers of neural states has been implemented in silicon and results are presented. The circuits demonstrated confront many of the issues that blight massively parallel analog systems, and offer solutions
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
In this paper a reconfigurable analog VLSI neural network architecture is presented. The analog arch...
The pulse-stream technique, which represents neural states as sequences of pulses, is reviewed. Seve...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
Kaulmann T, Ferber M, Witkowski U, Rückert U. Analog VLSI Implementation of Adaptive Synapses in Pul...
Goser K, Hilleringmann U, Rückert U, Schumacher K. VLSI Technologies for Artificial Neural Networks....
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
Future development of neural networks and their applications will be strongly affected by the availa...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
This paper describes a complete silicon implementation of an Artificial Neural Network based on Cohe...
Engineering neural network systems are best known for their abilities to adapt to the changing chara...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
The recent resurgence of interest in neural networks (NNs) has resulted in the application of NNs t...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
In this paper a reconfigurable analog VLSI neural network architecture is presented. The analog arch...
The pulse-stream technique, which represents neural states as sequences of pulses, is reviewed. Seve...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
Kaulmann T, Ferber M, Witkowski U, Rückert U. Analog VLSI Implementation of Adaptive Synapses in Pul...
Goser K, Hilleringmann U, Rückert U, Schumacher K. VLSI Technologies for Artificial Neural Networks....
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
Future development of neural networks and their applications will be strongly affected by the availa...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
This paper describes a complete silicon implementation of an Artificial Neural Network based on Cohe...
Engineering neural network systems are best known for their abilities to adapt to the changing chara...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
The recent resurgence of interest in neural networks (NNs) has resulted in the application of NNs t...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
Indiveri G, Chicca E. A VLSI neuromorphic device for implementing spike-based neural networks. Prese...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
In this paper a reconfigurable analog VLSI neural network architecture is presented. The analog arch...