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AN ANALOG CMOS IMPLEMENTATION OF A KOHONEN NETWORK WITH LEARNING CAPABILITY

AN ANALOG CMOS IMPLEMENTATION OF A KOHONEN NETWORK WITH LEARNING CAPABILITY

With the increase in the demand for AI-based embedded systems, developing specialized hardware for the implementation of a neural network…
Go to the profile of Atharva Karwande
Atharva Karwande
A VLSI DESIGN OF THE MINIMUM ENTROPY NEURON

A VLSI DESIGN OF THE MINIMUM ENTROPY NEURON

In pattern recognition, the maximization of the transformation from the input to the output of the system corresponds to minimize the mean…
Go to the profile of Kulkarnipranesh
Kulkarnipranesh
Back-Propagation Learning Algorithms for Analog VLSI Implementation

Back-Propagation Learning Algorithms for Analog VLSI Implementation

There are many VLSI implementations of Neural Networks in both digital and analog mode. The selection strongly depends on the application…
Go to the profile of Tejas Kolhe
Tejas Kolhe
A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection

A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection

When a conventional CNN is deployed or implemented on hardware, frequent access to off-chip memory causes slow processing and large amount…
Go to the profile of Atharva Karwande
Atharva Karwande
Trending Blogs
High-Performance CNN Accelerator on FPGA Using Unified Winograd-GEMM Architecture

High-Performance CNN Accelerator on FPGA Using Unified Winograd-GEMM Architecture

Deployment of CNNs on embedded systems with lower processing power and smaller power budget is a challenging task. Some recent studies in…
Go to the profile of Tejas Kolhe
Tejas Kolhe
HARDWARE ACCELERATORS FOR MACHINE LEARNING.

HARDWARE ACCELERATORS FOR MACHINE LEARNING.

In most of the Machine learning area deep neural network plays a very important role. Convolution Neural network is classic deep learning…
Go to the profile of Akshay Joshi
Akshay Joshi
AN ANALOG IMPLEMENTATION OF THE BOLTZMANN MACHINE WITH PROGRAMMABLE LEARNING ALGORITHMS

AN ANALOG IMPLEMENTATION OF THE BOLTZMANN MACHINE WITH PROGRAMMABLE LEARNING ALGORITHMS

INTRODUCTION
Go to the profile of Soham Kamble
Soham Kamble

A FPGA-based Hardware Accelerator for Multiple Convolutional Neural Networks.

In Field of Image processing and computer vision Convolution Neural Network plays a very important role in these recent days. A FPGA-based…
Go to the profile of Akshay Joshi
Akshay Joshi
Data Path Optimization
Sparse Systolic Tensor Array for Efficient CNN Hardware Acceleration

Sparse Systolic Tensor Array for Efficient CNN Hardware Acceleration

Convolutional neural networks can also have accelerated by data path optimization. Early CNN accelerators have implemented Systolic arrays…
Go to the profile of Kulkarnipranesh
Kulkarnipranesh

Optimizing FPGA-based Accelerator Design For Deep Convolutional Neural Networks

Loop unrolling can be utilized to improve the utilization of vast computation resources in FPGA devices. Unrolling along various loop…
Go to the profile of Soham Kamble
Soham Kamble
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