Viterbi algorithm
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Note: This course is being offered this summer by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. To...more
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This course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451, is offered in the spring. Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM...more
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This course is the second of a two-term sequence. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of Principles of Digital Communication I and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-d...more
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Writing a Recursive Power Set Function in Scheme, Using a Lambda Mapping Function that Cons-Es the Car to Every Element in the Power-Set of the Cdr to Make the Recursive Step in the Power-Set Function, Using a Let Binding to Cause Power-Set to Only Make One Recursive Call Rather than Two, Structure of a Let Binding, How Expressions Within a Let Binding Cannot Depend On Each Other Unless the Let* Keyword Is Used, How a Let Binding Is Compil...more
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Advice for Applying Machine Learning, Debugging Reinforcement Learning (RL) Algorithm, Linear Quadratic Regularization (LQR), Differential Dynamic Programming (DDP), Kalman Filter & Linear Quadratic Gaussian (LQG), Predict/update Steps of Kalman Filter, Linear Quadratic Gaussian (LQG)
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Bayesian Statistics and Regularization, Online Learning, Advice for Applying Machine Learning Algorithms, Debugging/fixing Learning Algorithms, Diagnostics for Bias & Variance, Optimization Algorithm Diagnostics, Diagnostic Example - Autonomous Helicopter, Error Analysis, Getting Started on a Learning Problem
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Joint Space Dynamics, Newton-Euler Algorithm, Inertia Tensor, Example, Newton-Euler Equations, Lagrange Equations, Equations of Motion
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Handout Information, Section Sign-up, Karel Commands, An Algorithm vs Program, Syntax of a Karel Program, Running a Karel Program, Creating Methods, SuperKarel, A for Loop, A While Loop, Karel Conditions, If Statement, Putting it All Together
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The Factor Analysis Model,0 EM for Factor Analysis, Principal Component Analysis (PCA), PCA as a Dimensionality Reduction Algorithm, Applications of PCA, Face Recognition by Using PCA
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Latent Semantic Indexing (LSI), Singular Value Decomposition (SVD) Implementation, Independent Component Analysis (ICA), The Application of ICA, Cumulative Distribution Function (CDF), ICA Algorithm, The Applications of ICA
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Selection Sort, Live Demo: Working/execution of the Code, Selection Sort Analysis, Insertion Sort Algorithm, Live Demo: Working/execution of Insertion Sort, Insertion Sort Analysis, Insertion vs Selection, Quadratic Growth of the Algorithm, Merge Sort, Merge Sort: Working/execution Demo, Merge Sort Code Explanation, Merge Sort Analysis, Quadratic vs Linear Arithmetic, Sort 'Race', Quick Sort Idea
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