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Huffman Encoding is one of the very simple algorithms to compress data. Even though it is very old and simple , it is still widely used (eg : in few stages of JPEG, MPEG etc). In this project you will implement huffman encoding and decoding. You can read up in Wikipedia or any other tutorial. Your system should accept a file and you require to form a binary (huffman) tree for the same. During the construction of huffman tree, use the priority queue to select nodes along with smallest frequencies. Just one time you have constructed the tree, traverse the tree and create a dictionary of codewords (letter to code). Provided any new sentences, your system must show how the sentence is converted to huffman code and then decoded back to original sentence. Note that you must implement BST and Heap yourself and must not rely on any language libraries. You can use external libraries like GraphViz to display your huffman tree.
Each of the comparison in the binary search decrease the number of possible candidates where the key value can be searched by a factor of 2 as the array is divided into two halves
Data array A has data series from 1,000,000 to 1 with step size 1, which is in perfect decreasing order. Data array B has data series from 1 to 1,000,000, which is in random order.
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A B-tree of minimum degree t can maximum pointers in a node T pointers in a node.
give some examples of least cost branch and bound method..
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1. Using the traditional method of CPM: a. What activities are on the critical path? b. What is the expected total lead time of the project? 2. Using CCPM: a. What
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