'Output sequence' diaporamas de présentation

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The EM algorithm

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The EM algorithm

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Outline of the Chapter

Software Testing and Quality Assurance Theory and Practice Chapter 10 Test Generation from FSM Models. Outline of the Chapter. State-oriented Model Points of Control and Observation Finite-state Machine (FSM) Test Generation from an FSM Transition Tour Method Testing with State Verification

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FSA and HMM

FSA and HMM. LING 572 Fei Xia 1/5/06. Outline. FSA HMM Relation between FSA and HMM. FSA. Definition of FSA. A FSA is Q: a finite set of states ? : a finite set of input symbols I: the set of initial states F: the set of final states

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By: Dr. Uri Mahlab

Simulation in Digital Communication. By: Dr. Uri Mahlab. Chapter # 2 Random Processes. By: Dr. Uri Mahlab. Generation of Random Variables. Most computer software libraries include a uniform random number generator. Such a random number generator a number

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Corpora and Statistical Methods Lecture 8

Corpora and Statistical Methods Lecture 8. Albert Gatt. Part 2. Markov and Hidden Markov Models: Conceptual Introduction. In this lecture. We focus on (Hidden) Markov Models conceptual intro to Markov Models relevance to NLP Hidden Markov Models algorithms. Acknowledgement.

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Forward-backward algorithm

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Convolution codes ? ????

Chapter 8. Convolution codes ? ????. ?? . ?????? . SHNU. Linear codes: 1 infor. bit ? 1 codeword; (n,k)or [n,k,d] ? k-bit infor. ? one n-bit codeword Convolution code: . 1 infor. bit ? m codewords ; (n,k,m) k-bit infor.+ m previous infor.bits ? 1 n-bit codeword

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Capabilities, Minimization, and Transformation of Sequential Machines

Capabilities, Minimization, and Transformation of Sequential Machines. Finite-state Model. Deterministic machines: next state S ( t +1) determined uniquely by present state S ( t ) and present input x ( t ) S ( t +1) = { S ( t ), x ( t )} : state transition function

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Sorting and Selection

Sorting and Selection. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Lower Bounds. Lower bound : an estimate on a minimum amount of work needed to solve a given problem Examples:

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APPENDIX D R ANDOM N UMBER G ENERATION

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) items with keys in the range [0, N - 1]

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) items with keys in the range [0, N - 1]

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) entries with keys in the range [0, N - 1]

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) entries with keys in the range [0, N - 1]

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) entries with keys in the range [0, N - 1]

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Bucket-Sort and Radix-Sort

Bucket-Sort and Radix-Sort. 1, c. 3, a. 3, b. 7, d. 7, g. 7, e. ?. ?. ?. ?. ?. ?. ?. 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. B. Let be S be a sequence of n (key, element) items with keys in the range [0, N - 1]

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