Lectures related to Nature of Extremum Points

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

Focuses on determining local extremum points of functions through various examples.

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

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

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

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

Covers the conditions for finding absolute extrema in multivariable functions.

Discusses local extrema of functions in two variables around the point (0,0).

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

Explores Taylor's formula, polynomials, functions, and series applications.

Explores the desirability and decorability of function extremes and asymptotes.

Discusses generalized fine increments, function evaluation, theorems, and derivative applications.

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

Covers necessary conditions for extrema and provides illustrative examples.

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

Explores real functions, covering parity, periodicity, and polynomial functions.

Covers limits, continuity, and the intermediate value theorem in functions.

Covers the concept of extrema of functions, including local and global maxima and minima.

Explores trigonometric derivatives, composition of functions, and inflection points in differential calculation.

Covers the concept of continuity, providing examples and definitions of continuous functions.