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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...

Loop Optimization Techniques in Compiler Design

LOOP Optimization

Rules Every Programmer must follow before the optimization of any source code. 
1.) Loop transformation technique. 
2.) Help to reduce optimize the execution time of a program.
3.) Basically, remove the iterations. 
4.) Loop Unrolling increase the program speed by eliminating loop control instructions.

Loop Optimization is a Machine Independent Technique. We can do Code optimization in the loops of the program. In loop optimization, code optimization is performed on inner loops.

Methods of Loop Optimization
1.) Code Motion
2.) Loop Invariant Method
3.) Loop Jamming
4.) Loop Unrolling
5.) Strength Reduction
Code Motion: Technique that moves the code outside the loop.
Loop Jamming: Combining two or more loops in a single loop.
Code Strength: Expressions that consumes CPU time and memory should replace with cheaper expressions. Replace Expensive Expressions (i.e., *) with cheaper ones (i.e., +)


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