Statistical coding techniques have been used for lossless statistical data compression, applying methods such as Ordinary, Shannon, Fano, Enhanced Fano, Huffman and Shannon-Fano-Elias coding methods. A new and improved coding method is presented, the Fano-Huffman Based Statistical Coding Method. It holds the advantages of both the Fano and Huffman coding methods. It is more easily applicable th...

A new method for constructing minimum-redundancy prefix codes is described. This method does not explicitly build a Huffman tree; instead it uses a property of optimal codes to find the codeword length of each weight. The running time of the algorithm is shown to be O(nk), which is asymptotically faster than Huffman’s algorithm when k = o(log n), where n is the number of weights and k is the nu...

Huffman coding is a widely used method for lossless data compression because it optimally stores data based on how often the characters occur in Huffman trees. An n-ary Huffman tree is a connected, cycle-lacking graph where each vertex can have either n “children” vertices connecting to it, or 0 children. Vertices with 0 children are called leaves. We let hn(q) represent the total number of n-a...

This work presents (s, c)-Dense Code, a new method for compressing natural language texts. This technique is a generalization of a previous compression technique called End-Tagged Dense Code that obtains better compression ratio as well as a simpler and faster encoding than Tagged Huffman. At the same time, (s, c)-Dense Code is a prefix code that maintains the most interesting features of Tagge...

Novel maximal coding compression techniques for the most important file-the text file of any full-text retrieval system are discussed in this paper. As a continuation of our previous work, we show that the optimal maximal coding schemes coincide with the optimal uniquely decodable coding schemes. An efficient algorithm generating an optimal maximal code (or an optimal uniquely decodable code) i...

A speech/audio codec based on Frequency Domain Linear Prediction (FDLP) exploits auto-regressive modeling to approximate instantaneous energy in critical frequency sub-bands of relatively long input segments. The current version of the FDLP codec operating at 66 kbps has been shown to provide comparable subjective listening quality results to state-of-theart codecs on similar bit-rates even wit...

Lossy JPEG compression is a widely used compression technique. Normally the JPEG standard technique uses three process mapping reduces interpixel redundancy, quantization, which is lossy process and entropy encoding, which is considered lossless process. In this paper, a new technique has been proposed by combining the JPEG algorithm and Symbol Reduction Huffman technique for achieving more com...

While compressing a file with a Huffman code, it is possible that the size of the file grows temporarily. This happens when the source letters with low frequencies (to which long codewords are assigned) are encoded first. The maximum data expansion is the average growth in bits per source letter resulting from the encoding of a source letter with a long codeword. It is a measure of the worst ca...

Individuals with severe motor impairments commonly enter text using a single binary switch and symbol scanning methods. We present a new scanning method -Huffman scanning - which uses Huffman coding to select the symbols to highlight during scanning, thus minimizing the expected bits per symbol. With our method, the user can select the intended symbol even after switch activation errors. We des...

We study a special case of Hamming-Huffman trees, in which both data compression and error detection are tackled on the same structure. Given hypercube Q n dimension , we interested some aspects its vertex neighborhoods. For subset L vertices neighborhood is defined as union neighborhoods . The minimum problem that determining cardinality over all those sets This well-known has already been sol...