Abstract

Problem statement: Boolean function classification plays an important role in the field like technology mapping for digital circuit design, function mapping for minimization and the development of universal logic modules. Approach: In this study, we present a single core hardware module to implement Boolean function classification techniques on Altera FLEX10K FPGA device for lossless data compression. The compression algorithm was performed by incorporating Boolean function classification into Huffman coding. This allows compression that was more efficient because the data had been categorized and simplified before the encoding was done. Simulation, timing analysis and circuit synthesis were commenced to verify the functionality and performance of the designated circuits which supports the practicality, advantages and effectiveness of the proposed single core hardware implementation. Results: The result shows a higher compression ratio. The average compression ratio was 25-37.5% from numerous testing with various text inputs with a maximum clock frequency of 27.9 MHz. Conclusion: The hardware implementation demonstrated complete, correct functionality and met all the initial system requirements.

Highlights

  • The term Data Compression refers to the process of reducing the amount of the required data representing a given quantity of information

  • Boolean function classification technique has been traditionally designed for digital circuit applications

  • Boolean function classification plays an important role in the field like technology mapping for digital circuit design, function

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Summary

INTRODUCTION

Mapping for minimization and the development of universal logic modules (Chang and Falkowski, 1996). When there is no more unmatched data source with the is started by building a statistical lookup table for all the fractal, the algorithm continues with the Huffman possible text inputs, ranging from a to z for small case, encoding to compress the classified data source. The data input is The possible length of the encoded output ranges from classified and compressed into another form. The best compression ratio for this algorithm is 87.5%, which is the case when all the inputs are having encoded output of 1 bit. This rarely occurs since text inputs usually consist of various different characters, which have their respective class and output bits as defined in the lookup table.

Cells in logic mode Cells in cascade mode
Findings
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