[b][size=85][color=#333333]A [url=https://perso.liris.cnrs.fr/nicolas.pronost/UUCourses/ElementaryMathsGMT/01%20Calculus/Calculus%203/Calculus%203.1%20-%20Multivariable%20calculus%20-%20Lecture.pdf]stationary point[/url] of a function of two (or [b][size=85][color=#333333]multiple[/color][/size][/b]) variables is a point at which all partial derivatives are zero and can be a [/color][color=#cc4125]local [/color][color=#ff0000]maximum[/color][color=#333333], [/color][color=#0000ff]minimum[/color][color=#333333], or [/color][color=#38761d]saddle point[/color][color=#333333].[br] As a [url=https://www.geogebra.org/m/c5rhh2tz]numerically specified function[/url], we consider the intensity distribution of the diffraction field when light is diffracted by a single slit: J=J(x,y). The order of operations is the same as for the explicit set function discussed in applet [url=https://www.geogebra.org/m/te2vqwjq]1[/url]. The algorithms for finding [color=#ff0000]max[/color] / [color=#0000ff]min[/color] can be found in applet [url=https://www.geogebra.org/m/ef6s3hyj]2[/url], and the algorithm for finding a [color=#6aa84f]saddle point[/color] can be found in applet [url=https://www.geogebra.org/m/hcgdjdyf]3[/url]. Algorithm for finding the expected locations of Local maxima, minima or saddle points of stationary points of a numerical function of two variables in the coordinate descent-ascent method in [url=https://www.geogebra.org/m/t55drncf]4[/url].[br][/color][/size][/b]

[sup]*[/sup] [size=85][b]Some Images of the applet of the application of the descent-ascent algorithm of coordinates for the calculation of stationary points of the numerical function f(x,y) in the case of finding a saddle point can be found in the [url=https://www.geogebra.org/m/mh4xu32k]applet[/url].[/b][/size]