Lectures related to Chicken (Scheme implementation)

Diffusion-Convection: Modeling and Schemes

Covers modeling and numerical schemes for diffusion-convection problems.

Explains the Runge-Kutta methods, particularly the explicit scheme of order 4 (ERK4), and how to optimize parameters for accuracy.

Runge-Kutta Methods: Approximating Differential Equations

Covers the stages of the explicit Runge-Kutta method for approximating y(t) with detailed explanations.

Newmark-B Method Stability

Covers the stability analysis of the Newmark-B method and its implementation.

Advanced Numerical Analysis: Space Discretization

Explores advanced space discretization techniques in numerical analysis for solving differential systems efficiently and accurately.

Wave Equation: Numerical Methods

Explores numerical methods for solving the wave equation, discussing stability conditions and convergence rates.

Numerical Analysis: Implicit Schemes

Covers implicit schemes in numerical analysis for solving partial differential equations.

Lazy Evaluation: Introduction and Examples

Covers lazy evaluation, memoization, interpreter implementation, code generation challenges, and potential extensions.

Programming with Parallelograms

Covers the implementation of a Parallelogram class in Python.

Stability of Newmark-B Method

Discusses the stability of the Newmark-B method and time integration with external forces.

Metropolis-Hastings Algorithm: Implementation and Case Study

Explores the Metropolis-Hastings algorithm and its application in a transportation mode choice model.

Implementing a Python Calculator

Covers the implementation of a Python calculator with various arithmetic operations.

Data Science with Python: Numpy Basics

Introduces the basics of Numpy, a numerical computing library in Python, covering advantages, memory layout, operations, and linear algebra functions.

Implicit Conversion: Core Concepts

Covers the core concepts of implicit conversion in Scala and its implementation in Scala code.

High Order Methods: Space Discretisation

Covers high order methods for space discretisation in linear differential systems.

Implicit Euler Scheme

Explains the Implicit Euler Scheme, a method for solving differential equations numerically, focusing on stability and convergence properties.

Finite Difference Grids

Explains finite difference grids for computing solutions of elastic membranes using Laplace's equation and numerical methods.

Functional Reactive Programming: Signals and Transformations

Explores functional reactive programming using signals to simplify state changes and event reactions in a more functional and clean approach.

Matrix Operations: Multiplication and Identity

Covers matrix operations in Python, focusing on multiplication and identity matrix generation.

Heat Equation in 1D: Chapter 12

Explores the heat equation in 1D, emphasizing conservation of thermal energy and numerical solution methods.