A methodology to design a digital special purpose neurocomputer implementing feedforward multilayer neural networks is presented. The design flow consists of three stages: the weight discretization, which relaxes the precision requirements maintaining the compatibility with the original model; the architectural synthesis, which transforms the abstract description into an optimized digital structure; and the VHDL model generation, which produces the VHDL description of the general purpose neurocomputer by using a set of parametric components
This work used the Summit Visual HDL for VHDL – a Visual Hardware Description package which com-pile...
Introduction This chapter describes a methodology for designing digital VLSI neurochips which emphas...
Ramacher U, Rückert U. VLSI Design of Neural Networks. Boston: Kluwer Academic Publishers; 1991
A methodology to design a digital special purpose neurocomputer implementing feedforward multilayer ...
This paper presents an automatic design flow for digital special purpose feed-forward multi-layer ne...
The authors consider digital VLSI implementation of layered feedforward neural networks. The main go...
Artificial neural networks are extended on the basis of brain structure. Like the brain, ANNs can re...
This brief presents a novel high-performance architecture for implementation of custom digital feed ...
A tool for automatic synthesis of neural network structures to programmable hardware components is i...
The last decade has witnessed the revival and a new surge in the field of artificial neural network ...
In this paper we present a system for automatic synthesis of special purpose hardware for neural net...
This thesis aims to understand how to design high performance, flexible and cost effective neural co...
In this paper a hardware implementation of a neural network using Field Programmable Gate Arrays (FP...
Presents a synthesis methodology for the automated design of single and multi-chip processors implem...
In this paper we present a system for automatic synthesis of special purpose hardware for neural net...
This work used the Summit Visual HDL for VHDL – a Visual Hardware Description package which com-pile...
Introduction This chapter describes a methodology for designing digital VLSI neurochips which emphas...
Ramacher U, Rückert U. VLSI Design of Neural Networks. Boston: Kluwer Academic Publishers; 1991
A methodology to design a digital special purpose neurocomputer implementing feedforward multilayer ...
This paper presents an automatic design flow for digital special purpose feed-forward multi-layer ne...
The authors consider digital VLSI implementation of layered feedforward neural networks. The main go...
Artificial neural networks are extended on the basis of brain structure. Like the brain, ANNs can re...
This brief presents a novel high-performance architecture for implementation of custom digital feed ...
A tool for automatic synthesis of neural network structures to programmable hardware components is i...
The last decade has witnessed the revival and a new surge in the field of artificial neural network ...
In this paper we present a system for automatic synthesis of special purpose hardware for neural net...
This thesis aims to understand how to design high performance, flexible and cost effective neural co...
In this paper a hardware implementation of a neural network using Field Programmable Gate Arrays (FP...
Presents a synthesis methodology for the automated design of single and multi-chip processors implem...
In this paper we present a system for automatic synthesis of special purpose hardware for neural net...
This work used the Summit Visual HDL for VHDL – a Visual Hardware Description package which com-pile...
Introduction This chapter describes a methodology for designing digital VLSI neurochips which emphas...
Ramacher U, Rückert U. VLSI Design of Neural Networks. Boston: Kluwer Academic Publishers; 1991