Huffman codes
1.In telecommunication, how do we represent a set of messages, each with an access frequency, by a sequence of 0 s and 1 s?
2.To minimize the transmission and decoding costs, we may use short strings to represent more frequently used messages.
3.This problem can be solved by using an extended binary tree which is used in the 2-way merging problem.
the sourse code is
to encode and decode the Huffman.
Traveling Salesperson Problem
Our branch-and-strategy splits a branch and bound solution into two groups:
one group including a particular arc and the other excluding this arc.
1.Each splitting incurs a lower bound and we shall traverse the searching tree with the "lower" lower bound.
2.If a constant subtracted from any row
or any column of the cost matrix, an
optimal solution does not change.
) Compression using huffman code
-with a number of bits k per code word
-provide huffman table
Huffman coding is optimal for a symbol-by-symbol coding with a known input probability distribution.This technique uses a variable-length code table for encoding a source symbol. The table is derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol .Huffman coding uses a specific method for representing each symbol, resulting in a prefix code that expresses the most common characters using shorter strings of bits than those used for less common source symbols.The Huffman coding is a procedure to generate a binary code tree.
The emphasis of this book is on real-time application of Synopsys tools, used
to combat various problems seen at VDSM geometries. Readers will be
exposed to an effective design methodology for handling complex, submicron
ASIC designs. Significance is placed on HDL coding styles,
synthesis and optimization, dynamic simulation, formal verification, DFT
scan insertion, links to layout, physical synthesis, and static timing analysis.
At each step, problems related to each phase of the design flow are identified,
with solutions and work-around described in detail. In addition, crucial issues
related to layout, which includes clock tree synthesis and back-end
integration (links to layout) are also discussed at length. Furthermore, the
book contains in-depth discussions on the basics of Synopsys technology
libraries and HDL coding styles, targeted towards optimal synthesis solution.
JXMLEditor is a XML editor developed in Java which is based on the Xerces Java parser. The goal of this editor is to offer some features (tree view, drag & drop, syntax colorizing) to create XML documents easily. Also available as Eclipse Plugin.
Abtract - We propose a new family of fi lter banks,
named NDFB, that can achieve the directional decomposition
of arbitrary N-dimensional (N ≥ 2) signals with a simple and
effi cient tree-structured construction.
The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported.
