Write A Program For Huffman Coding
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Programming Microcontrollers in C
Ted Van Sickle spent over fifteen years at Motorola as a microcontroller specialist. He now consults and teaches classes on software design and programming for microcontroller systems. He holds a MSEE from the University of Michigan.Introduces microcontrollers and describes their programming environment, offering tips on coding for microcontrollersDescribes techniques to get maximum performance from your codeDiscusses the differences between 8-bit and larger microcontrollers, giving application examples and providing details on using different compilers
Introduction to Data Compression
Introduction to Data Compression, Fifth Edition, builds on the success of what is widely considered the best introduction and reference text on the art and science of data compression. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio and video. This new edition includes all the latest developments in the field. Khalid Sayood provides an extensive introduction to the theory underlying today's compression techniques, with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, the book includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, and scalar and vector quantization. The book provides a comprehensive working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package. - Explains established and emerging standards in- depth, including JPEG 2000, JPEG-LS, MPEG-2, H.264, JBIG 2, ADPCM, LPC, CELP, MELP, iLBC and the new HEVC standard - Includes more coverage of lattices in vector quantization - Contains improved and expanded end-of-chapter problems - Source code is provided via a companion website that gives readers the opportunity to build their own algorithms and choose and implement techniques in their own applications
Introduction to Coding and Information Theory
Author: Steven Roman
language: en
Publisher: Springer Science & Business Media
Release Date: 1996-11-26
This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.