Lectures related to Convergence Criteria

Explains the Jacobi and Gauss-Seidel methods for solving linear systems iteratively.

Nonlinear Equations: Fixed Point Method Convergence

Covers the convergence of fixed point methods for nonlinear equations, including global and local convergence theorems and the order of convergence.

Descent methods and line search: Finiteness of the line search algorithm

Explores the Wolfe conditions for line search algorithms and proves the finiteness of the line search parameter.

Resolution Sequence: Defining a Procedure

Explains the systematic procedure for solving flow sheets and stream calculations.

Lambda Functions: Examples

Explores lambda functions in Java through practical examples and the consumer interface.

Photo Maquette

Explores the importance of photo maquette in the creative process.

Exploration Bias

Explores regularization, learning algorithms, and subgaussian assumptions in machine learning.

Convergence Analysis: Iterative Methods

Covers the convergence analysis of iterative methods and the conditions for convergence.

Fixed Point Theorem: Convergence of Newton's Method

Covers the fixed point theorem and the convergence of Newton's method, emphasizing the importance of function choice and derivative behavior for successful iteration.

Value Iteration Acceleration: PID and Operator Splitting

Explores accelerating the Value Iteration algorithm using control theory and matrix splitting techniques to achieve faster convergence.

Loops: Iteration and Simplification

Covers the concept of loops in programming, including for, while, and do-while loops.

Fixed-Point Methods: Convergence Analysis

Discusses fixed-point methods, convergence analysis, error control, and high-order methods.

Datapath Design: Mandelbrot & Fixed-Point

Explores datapath design for Mandelbrot set and fixed-point number representation in digital systems.

Fixed Point Method

Covers the fixed point method for convergence and linear error reduction.

Bisection Method: Example

Focuses on using the bisection method to approximate function roots with precision.

Image Coding Optimization

Demonstrates the optimization of image coding by creating a compressed image list.

Collections: Iterators

Explains how to use iterators in Java collections to iterate over list elements.

Higher Order Methods: Iterative Techniques

Covers higher order methods for solving equations iteratively, including fixed point methods and Newton's method.

Root Finding Methods: Secant and Newton's Methods

Covers numerical methods for root finding, focusing on the secant and Newton's methods.

Infinite-Horizon Problems: Formulation & Complexity

Covers infinite-horizon problems in Applied Probability and Stochastic Processes.