
While lossy compression techniques are used for images, sound. where feature reproduction is more important than the actual data, it is necessary to use lossless compression for certain files containing data, programmes. Lossless compression techniques are not as effective as lossy ones and usually require a lot of computation for both compression and decompression. We presented a novel lossless compression techniques based on linear feedback shift registers. The advantage of this technique is that decompression is fairly simple and can be implemented without extensive computations. The decompression algorithm is also useful for implementation in hardware. In this paper we presented the details of the LFSR based algorithm. The results on various types of data such as images, sound files and text files presented and the results compared against existing lossless compression techniques.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
