Add to ORKGAbstract- This paper presents a new VLSI archi-tecture for ANNs based on the combination of digital signalling and analog computing. It achieves a high level of parallelism as well as ecient area and power usage making very large networks possible. An imple-mentation is presented combining 33k synapses and 256 neurons on 9 mm2 of silicon area. I
The electrophysiological behavior of real neurons is emulated by the silicon neuron. The network of ...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...
A reconfigurable mixed-mode perceptron building block for VLSI Neural Networks is presented. The pro...
The first description of ANN integrated circuit implements a continuous time analog circuit for AM. ...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
Heittmann A, Rückert U. Mixed mode VLSI implementation of a neural associative memory. In: Microele...
A highly parallel array architecture for ANN algorithms is presented and evaluated. The array, consi...
Future development of neural networks and their applications will be strongly affected by the availa...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
There are several neural network implementations using either software, hardware-based or a hardware...
Multi-layer feed-forward neural networks have the capability to classify and generalize, which are n...
Heittmann A, Rückert U. Mixed Mode VLSI Implementation of a Neural Associative Memory. Analog Integr...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
A board is described that contains the ANN A neural-network chip, and a DSP32C digital signal proces...
The electrophysiological behavior of real neurons is emulated by the silicon neuron. The network of ...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...
A reconfigurable mixed-mode perceptron building block for VLSI Neural Networks is presented. The pro...
The first description of ANN integrated circuit implements a continuous time analog circuit for AM. ...
A compact neural network architecture using a hybrid digital-analog design is implemented in Very La...
Heittmann A, Rückert U. Mixed mode VLSI implementation of a neural associative memory. In: Microele...
A highly parallel array architecture for ANN algorithms is presented and evaluated. The array, consi...
Future development of neural networks and their applications will be strongly affected by the availa...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
There are several neural network implementations using either software, hardware-based or a hardware...
Multi-layer feed-forward neural networks have the capability to classify and generalize, which are n...
Heittmann A, Rückert U. Mixed Mode VLSI Implementation of a Neural Associative Memory. Analog Integr...
Rapid advances in the semiconductor industry have provided the technologies for the implementation o...
A board is described that contains the ANN A neural-network chip, and a DSP32C digital signal proces...
The electrophysiological behavior of real neurons is emulated by the silicon neuron. The network of ...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Abstract. The usefulness of an articial analog neural network is closely bound to its trainability. ...