ELEC-E8101: Digital and Optimal Control-Stability of discrete-time systems In the previous lecture. . . We Discretized a continuous-time system in a state-space form to its discrete counterpar...
ELEC-E8101: Digital and Optimal Control State-space representation In the previous lecture. . . We ■ Designed practical PID controllers for applications ■ Designed anti-windup schemes to avoid wi...
ELEC-E8101: Digital and Optimal Control-Discrete PID controllers In the previous lecture. . . We Discussed what happens to the signal when sampling Derived what is the sampling frequency so ...
Supervised Machine Learning Lecture 4 Model selection Model selection and Occam’s Razor Occam’s razor principle “Entities should not be multiplied unnecessarily” captures the trade-off between...
Digital and Optimal Control: Discretization In the previous lecture. . . We Discussed the importance of z-transforms for analyzing discrete-time systems Derived and used the properties of z-t...
Embedded Real Time Systems 3 Memory Technology Agenda What is memory and the origins How does RAM work Memory access and hierarchy Essential Questions What is memory and how it works? ...
Supervised Machine Learning Lecture 3: Learning with infinite hypothesis classes Recall: PAC learnability A class 𝐶 is PAC-learnable, if there exist an algorithm 𝒜 that given a training s...
Embedded Real-Time Systems 2 Essentials of processor architecture Agenda Motivation Von Neuman Architecture and its elements CPU elements and instruction processing Inputs and Outputs ma...
Supervised Machine Learning 2 4 small error high probability first important fomula start point