Lectures related to Local Extrema of Functions

Discusses optimization techniques, focusing on local and global extrema in functions.

Covers advanced optimization methods using Lagrange multipliers to find extrema of functions subject to constraints.

Covers Taylor's formula, developments, and extrema of functions, discussing convexity and concavity.

Explores techniques for minimizing functions and finding critical points.

Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.

Covers the optimization of functions, focusing on finding the maximum and minimum values.

Covers Morse theory, focusing on critical points and non-degeneracy.

Explains how to find local extrema of functions using derivatives and critical points.

Covers the method of Lagrange multipliers to find extrema subject to constraints.

Explores the conditions for local extrema of functions in several variables, including critical points and the Hessian matrix.

Covers the Implicit Functions Theorem, explaining how equations can define functions implicitly.

Covers the statement of the Bernoulli's Hospital Rule and its application.

Explores limits, continuity, and uniform continuity in functions, including properties at specific points and closed intervals.

Covers the conditions for finding absolute extrema in multivariable functions.

Covers the optimization of functions, focusing on finding the maximum and minimum values over a given domain.

Explores the integration by parts technique through examples, showcasing its step-by-step application to functions like cos(x) and sin(x.

Explains extrema of functions in several variables, stationary points, saddle points, and the role of the Hessian matrix.

Covers the Implicit Functions Theorem, providing a general understanding of implicit functions.

Discusses advanced analysis concepts, focusing on differential equations and timers in microcontrollers.

Covers the properties and operations of convex functions.