In this paper, a mixed-signal current-mode chip is imple- mented using commercial 0.35 pm technology. It performs the preprocessing task done by the first neurons layers in ART-based neural networks. Post layout simulations show an acceptable linearity error for such neural systems. The input signal swings from 20 to 50 microampere. The circuit operates at a supply voltage of 3.3 V with 200 kHz bandwidth
Developing mixed-signal analog-digital neuromorphic circuits in advanced scaled processes poses sign...
An analogue circuit implementation is presented for an adaptive resonance theory neural network arch...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi lay...
The CMOS circuit implementation of the feedforward neural primitives of a generic Multi Layer Percep...
The CMOS circuit implementation of the feed forward neural primitives of a generic Multi Layer Perce...
Explores the design of cellular neural networks (CNN) by using sampled-data analog current-mode tech...
An architecture and related building blocks are presented for the realization of image processing ta...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
This paper presents a VLSI circuit implementation for both the short-term memory (STM) and long-term...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
There are several possible hardware implementations of neural networks based either on digital, anal...
This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
The design of a CMOS focal plane array with 128 x 128 pixels and analog neural preprocessing is pres...
In this paper an analogue two-quadrant multiplier suited for the implementation of large arrays of m...
Developing mixed-signal analog-digital neuromorphic circuits in advanced scaled processes poses sign...
An analogue circuit implementation is presented for an adaptive resonance theory neural network arch...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi lay...
The CMOS circuit implementation of the feedforward neural primitives of a generic Multi Layer Percep...
The CMOS circuit implementation of the feed forward neural primitives of a generic Multi Layer Perce...
Explores the design of cellular neural networks (CNN) by using sampled-data analog current-mode tech...
An architecture and related building blocks are presented for the realization of image processing ta...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
This paper presents a VLSI circuit implementation for both the short-term memory (STM) and long-term...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
There are several possible hardware implementations of neural networks based either on digital, anal...
This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
The design of a CMOS focal plane array with 128 x 128 pixels and analog neural preprocessing is pres...
In this paper an analogue two-quadrant multiplier suited for the implementation of large arrays of m...
Developing mixed-signal analog-digital neuromorphic circuits in advanced scaled processes poses sign...
An analogue circuit implementation is presented for an adaptive resonance theory neural network arch...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...