The mathematical neuron basic cells used as basic cells in popular neural network architectures and algorithms are discussed. The most popular neuron models (without training) used in neural network architectures and algorithms (NNA) are considered, focusing on hardware implementation of neuron models used in NAA, and in emulation of biological systems. Mathematical descriptions and block diagram representations are utilized in an independent approach. Nonoscillatory and oscillatory models are discusse
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
In this chapter, we present an overview of the recent advances in analog-to-digital converter (ADC) ...
A hardware neuron that can generate a broad class of activation functions is introduced. The require...
Artificial neural networks are systems composed of interconnected simple computing units known as a...
A CMOS circuit is proposed that emulates FitzHugh-Nagumo's differential equations using OTAs, diode ...
Abstract —A complete derivation of neuron model is presented, starting with the description of the f...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
This final year project is about the VLSI implementation of a neuron. It introduces the development ...
A few individual design examples of programmable device-based biological neuron model implementation...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
Engineering neural network systems are best known for their abilities to adapt to the changing chara...
Abstract:There is various new & advance technologies in medical science we are trying to process...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
The Letter presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
In this chapter, we present an overview of the recent advances in analog-to-digital converter (ADC) ...
A hardware neuron that can generate a broad class of activation functions is introduced. The require...
Artificial neural networks are systems composed of interconnected simple computing units known as a...
A CMOS circuit is proposed that emulates FitzHugh-Nagumo's differential equations using OTAs, diode ...
Abstract —A complete derivation of neuron model is presented, starting with the description of the f...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
This final year project is about the VLSI implementation of a neuron. It introduces the development ...
A few individual design examples of programmable device-based biological neuron model implementation...
Nature has evolved highly advanced systems capable of performing complex computations, adoption and ...
Engineering neural network systems are best known for their abilities to adapt to the changing chara...
Abstract:There is various new & advance technologies in medical science we are trying to process...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
The Letter presents two nonlinear CMOS current-mode circuits that implement neuron soma equations fo...
Artificial Neural Networks are powerful computational tools with many diverse applications in a vari...
In this chapter, we present an overview of the recent advances in analog-to-digital converter (ADC) ...
A hardware neuron that can generate a broad class of activation functions is introduced. The require...