Colloque avec actes et comité de lecture. internationale.International audienceThis paper describes a novel Multi-Chip Module (MCM) digital implementation of a reconfigurable multi-precision neural network classifier. The design is based on a scalable systolic architecture with a user defined topology and arithmetic precision of the neural network. Indeed, the MCM integrates 64/32/16 neurons with a corresponding accuracy of 4/8/16-bits. A prototype has been designed and successfully tested in CMOS 0.7 $\mu$m technology
A special-purpose chip, optimized for computational needs of neural networks and performing over 200...
Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lie...
Neural networks are a subset of machine learning that are currently rapidly being deployed for vario...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
Colloque avec actes et comité de lecture.In this paper a systolic multi-precision digital VLSI class...
A special purpose neural IC is described which will be utilised in a data-acquisition system in DESY...
In this letter, complementary metal–oxide–semiconductor (CMOS) implementation of a neural network (N...
The requirement for dense interconnect in artifi-cial neural network systems has led researchers to ...
This paper describes how to implement a partially connected neural network by Giga-Ops Spectrum G800...
There are several possible hardware implementations of neural networks based either on digital, anal...
With the advent of new technologies and advancement in medical science we are trying to process the ...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Simple nonlinear synapse circuit proposes fo r implementation of artificial neural networks using st...
A special-purpose chip, optimized for computational needs of neural networks and performing over 200...
Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lie...
Neural networks are a subset of machine learning that are currently rapidly being deployed for vario...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
This paper describes a novel MCM digital implementation of a reconfigurable multi-precision neural n...
Colloque avec actes et comité de lecture.In this paper a systolic multi-precision digital VLSI class...
A special purpose neural IC is described which will be utilised in a data-acquisition system in DESY...
In this letter, complementary metal–oxide–semiconductor (CMOS) implementation of a neural network (N...
The requirement for dense interconnect in artifi-cial neural network systems has led researchers to ...
This paper describes how to implement a partially connected neural network by Giga-Ops Spectrum G800...
There are several possible hardware implementations of neural networks based either on digital, anal...
With the advent of new technologies and advancement in medical science we are trying to process the ...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Simple nonlinear synapse circuit proposes fo r implementation of artificial neural networks using st...
A special-purpose chip, optimized for computational needs of neural networks and performing over 200...
Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lie...
Neural networks are a subset of machine learning that are currently rapidly being deployed for vario...