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Design and Implementation of Parallel MLP-Back Propagation Neural Network Technique for Image Compression and Decompression on FPGA


Affiliations
1 R.L Jalappa Institute of Technology, Bangalore, India
     

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Due to the increasing traffic caused by multimedia information and digitized form of representation of images, image compression become a necessity. The Parallel multilayer perceptron (MLP)[1] back propagation neural network Distributive Arithmetic (DA) architecture has a reduced latency and a good throughput. This design is twice faster than the simple Distributive Arithmetic Architecture and is thus suitable for applications that require high speed image processing algorithms and implemented using IP core and chipscope on vertex-2 Pro (2vp30- ff896-7).

Keywords

Parallel Back Propagation Neural Network (MLP), Distributive Arithmetic (DA), Look-Up Table (LUT), FIR Filter.
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  • Design and Implementation of Parallel MLP-Back Propagation Neural Network Technique for Image Compression and Decompression on FPGA

Abstract Views: 249  |  PDF Views: 2

Authors

V. Shilpakala
R.L Jalappa Institute of Technology, Bangalore, India
Vijay Kumar
R.L Jalappa Institute of Technology, Bangalore, India
K. Viswanath
R.L Jalappa Institute of Technology, Bangalore, India

Abstract


Due to the increasing traffic caused by multimedia information and digitized form of representation of images, image compression become a necessity. The Parallel multilayer perceptron (MLP)[1] back propagation neural network Distributive Arithmetic (DA) architecture has a reduced latency and a good throughput. This design is twice faster than the simple Distributive Arithmetic Architecture and is thus suitable for applications that require high speed image processing algorithms and implemented using IP core and chipscope on vertex-2 Pro (2vp30- ff896-7).

Keywords


Parallel Back Propagation Neural Network (MLP), Distributive Arithmetic (DA), Look-Up Table (LUT), FIR Filter.