Title :
Particle Algorithm for Lossless Data Compression
Author :
Shuai, Dianxun ; Zhang, Ping ; Zhang, Bin
Author_Institution :
East China Univ. of Sci. & Technol., Shanghai
Abstract :
This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. The basic conception, parallel algorithm, properties and realization scheme of GPM are discussed. The proposed GPM approach has advantages over other serial lossless compression methods in terms of parallelism, scalability and easy hardware implementation. GPM is suitable for the lossless compression based on various prediction models and higher-order transition models.
Keywords :
VLSI; computational complexity; data compression; encoding; parallel algorithms; particle swarm optimisation; systolic arrays; GPM approach; VLSI systolic array; generalized particle model; lossless data compression; parallel algorithm; particle algorithm; prediction coding; time complexity; Cellular neural networks; Context modeling; Data compression; Image coding; Information processing; Multimedia databases; Predictive coding; Predictive models; Quantization; Wavelet transforms;
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
DOI :
10.1109/ICSMC.2006.384716
