![]() ![]() Roark, Brian Fried-Oken, Melanie Gibbons, ChrisĬurrent scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. Huffman and linear scanning methods with statistical language models. Moreover, we proved that we can construct a Huffman-DHT easily by estimating the probability distribution of the term occurrence from a small number of sample documents. The experimental results indicated that it is most effective when the P2P system consists of about 30, 000 nodes and contains many documents. We evaluated this approach in experiments using a document collection and assessed its load balancing capabilities in P2P IR. Huffman-DHT is the first approach to adapt concepts of coding theory and term frequency distribution to load balancing. ![]() Throuth ID management, the Huffman-DHT balances the index registration accesses among peers and reduces load concentrations. In a Huffman-DHT, a frequent term is assigned to a short ID and allocated a large space in the node ID space in DHT. The new index uses an algorithm similar to Huffman coding with a modification to the DHT structure based on the term distribution. We devised a new distributed index, named Huffman-DHT, for P2P IR. Kurasawa, Hisashi Takasu, Atsuhiro Adachi, JunĪlthough a distributed index on a distributed hash table (DHT) enables efficient document query processing in Peer-to-Peer information retrieval (P2P IR), the index costs a lot to construct and it tends to be an unfair management because of the unbalanced term frequency distribution. Load Balancing Scheme on the Basis of Huffman Coding for P2P Information Retrieval In our compression technique, we have conducted evaluations using a representative set of applications and we have applied each technique to two major embedded processor architectures The Combined Compression Technique improves the compression ratio to 45% and 42% for ARM and MIPS, respectively. Using this technique, we improve the final compression ratios in comparison to the first technique to 46% and 45% for ARM and MIPS, respectively (including all overhead that incurs). Reencoding those bits can reduce the size of decoding tables by up to 40%. It investigates the benefits of reencoding unused bits (we call them reencodable bits) in the instruction format for a specific application to improve the compression ratio. The Instruction Re-encoding Technique is ISA-dependent. The average compression ratios achieved using this technique are 48% and 50% for ARM and MIPS, respectively. This technique improves the final compression ratio by more than 20% compared to other known schemes based on Huffman Coding. It splits the instructions into portions of varying size (called patterns) before Huffman coding is applied. The instruction Splitting Technique is instruction set architecture (ISA)-independent. It combines our previous techniques, Instruction Splitting Technique and Instruction Re-encoding Technique into new one called Combined Compression Technique to improve the final compression ratio by taking advantage of both previous techniques. Our technique reduces the size of the generated decoding table, which takes a large portion of the memory. In this article we introduce a novel and efficient hardware-supported compression technique that is based on Huffman Coding. Code compression is a means to alleviate the problem by providing substantial savings in terms of code size. It is often challenging and time consuming to fit an amount of required software functionality within a given hardware resource budget. The size of embedded software is increasing at a rapid pace. Huffman-based code compression techniques for embedded processors Iteration time of static Huffman algorithm for compress and decompress is faster than adaptif Huffman algorithm,but performance of adaptif Huffman algorithm is best. Variation of character occurs will decrease compression ratio. ![]() Thisresearch used static and adaptif Huffman algorithms to compress text data, and also compareit. Huffman algorithm is the most popular methods of text compression. Text compression algorithms are normally defined in terms of a source alphabet of 8-bit ASCII codes. Kompresi Data Menggunakan Algoritme HuffmanĪdisantoso, Julio Sulistio, Danny Dimas Silalahi, Bib Paruhum The Huffman encoder with whole audio-video system has been implemented in FPGA devices. The aim of design was to get as short binary stream as possible in this standard. Much attention has been paid to optimise the demand of hardware resources especially memory size. This article presents several hardware architectures of Advanced Audio Coding (AAC) Huffman noiseless encoder, its optimisations and working implementation. Huffman coding in advanced audio coding standard ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |