Neural Network Hardware Implementation Using FPGA

The FPGAs (Field Programmable Gate Arrays) approach for neural network implementation provides flexibility in programmable systems. For the neural based instrument prototype in real time application, conventional specific VLSI neural chip design suffers from the limitation in time and cost. With low

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Implementatıon of FFT and IFFT Algorithms in FPGA

This article explains implementing of Fast Fourier (FFT) and Inverse Fast Fourier Transform algorithms(IFFT) in FPGA. The reason of designing the study on FPGA base is that FPGAs are able to rearrange of logical blocks and moreover, mathematical algorithms can confirm faster

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Hardware Implementation of Wavelet Fuzzy Inference System with Evolutionary Learning

In this study, wavelet fuzzy system (WFS) together with its PSO-based learning is hardware implemented on FPGA. Floating point number format is used for the implementation considering its precision and dynamics. Although floating point numbers consume more hardware source than the other

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Implementation of an Hybrid Approach on FPGA for License Plate Detection Using Genetic Algorithm and Neural Networks

In this study, a hardware solution for car plate detection problem is proposed based on softcomputing techniques, namely the genetic algorithm and neural networks which are implemented on Programmable Field Gate Array (FPGA). The proposed plate detection requires a successful integration of

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