A 3-μm CMOS IC is presented demonstrating the concept of an analog neural system for constrained optimization. A serial time-multiplexed general-purpose architecture is introduced for the real-time solution of this kind of problem in MOS VLSI. This architecture is a fully programmable and reconfigurable one exploiting SC techniques for the analog part and making extensive use of digital techniques for programmability
A modular transconductance-mode (T-mode) design approach is presented for analog hardware implementa...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
The paper describes a multichip analog parallel neural network whose architecture, neuron characteri...
Architectures and circuit techniques for implementing general piecewise constrained optimization pro...
A modular reconfigurable serial architecture is presented for the analog/digital implementation of c...
A systematic approach for the design of analog neural nonlinear programming solvers using switched-c...
This paper explores whether analog circuitry can adequately perform constrained optimization. Const...
The design of neural network architectures is carried out using methods that optimize a particular o...
This paper is concerned with utilizing neural networks and analog circuits to solve constrained opti...
This paper deals with analog VLSI architectures addressed to the implementation of smart adaptive sy...
Increasing the energy efficiency of deep learning systems is critical for improving the cognitive ca...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
There are several possible hardware implementations of neural networks based either on digital, anal...
An ASIC analog chip which implements the basic computational primitives of a neural model with on-ch...
A modular transconductance-mode (T-mode) design approach is presented for analog hardware implementa...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
The paper describes a multichip analog parallel neural network whose architecture, neuron characteri...
Architectures and circuit techniques for implementing general piecewise constrained optimization pro...
A modular reconfigurable serial architecture is presented for the analog/digital implementation of c...
A systematic approach for the design of analog neural nonlinear programming solvers using switched-c...
This paper explores whether analog circuitry can adequately perform constrained optimization. Const...
The design of neural network architectures is carried out using methods that optimize a particular o...
This paper is concerned with utilizing neural networks and analog circuits to solve constrained opti...
This paper deals with analog VLSI architectures addressed to the implementation of smart adaptive sy...
Increasing the energy efficiency of deep learning systems is critical for improving the cognitive ca...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
There are several possible hardware implementations of neural networks based either on digital, anal...
An ASIC analog chip which implements the basic computational primitives of a neural model with on-ch...
A modular transconductance-mode (T-mode) design approach is presented for analog hardware implementa...
This paper discusses some of the limitations of hardware implementations of neural networks. The aut...
The paper describes a multichip analog parallel neural network whose architecture, neuron characteri...