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Introduction to Electrical Engineering & Computer Science (M-I-T)
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Lecture 12: Search Algorithms (M-I-T)
Lecture 12: Search Algorithms (M-I-T)
Course:
Introduction to Electrical Engineering & Computer Science (M-I-T)
Discipline:
Applied Sciences
Institute:
MIT
Instructor(s):
Dennis Freeman, Kendra Pugh
Level:
Undergraduate
Introduction to Electrical Engineering & Computer Science (M-I-T)
Lecture 10: Discrete Probability and State Estimation (M-I-T)
Lecture 12: Search Algorithms (M-I-T)
Lecture 13: Optimizing a Search (M-I-T)
Lecture 1: Object-Oriented Programming (M-I-T)
Lecture 2: Primitives, Combination, Abstraction, and Patterns (M-I-T)
Lecture 3: Signals and Systems (M-I-T)
Lecture 5: Characterizing System Performance (M-I-T)
Lecture 6: Designing Control Systems (M-I-T)
Lecture 7: Circuits (M-I-T)
Lecture 8: Op-Amps (M-I-T)
Lecture 9: Circuit Abstractions (M-I-T)
Recitation 10: Circuits: NVCC, Sample Problem (M-I-T)
Recitation 11: Op-Amps (M-I-T)
Recitation 12: Thevenin/Norton Equivalence and Superposition (M-I-T)
Recitation 13: Probability: Basics (M-I-T)
Recitation 14: Probability: State Estimation (M-I-T)
Recitation 15: Search: Basics (M-I-T)
Recitation 16: Search: Dynamic Programming, Costs and Heuristics (M-I-T)
Recitation 1: Object-Oriented Programming (M-I-T)
Recitation 8: Poles, Part II (M-I-T)