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Symbolic circuit analysis is a formal technique of circuit analysis to calculate the behaviour or characteristic of an electric/electronic circuit with the independent variables (time or frequency), the dependent variables (voltages and currents), and (some or all of) the circuit elements represented by symbols.
SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.
Mostly compatible with MATLAB. GAUSS: Aptech Systems 1984 21 8 December 2020: Not free Proprietary: GNU Data Language: Marc Schellens 2004 1.0.2 15 January 2023: Free GPL: Aimed as a drop-in replacement for IDL/PV-WAVE IBM SPSS Statistics: Norman H. Nie, Dale H. Bent, and C. Hadlai Hull 1968 23.0 3 March 2015: Not free Proprietary: Primarily ...
The following tables provide a comparison of computer algebra systems (CAS). [1] [2] [3] A CAS is a package comprising a set of algorithms for performing symbolic manipulations on algebraic objects, a language to implement them, and an environment in which to use the language.
Editing of mathematical expressions in two-dimensional form; plotting graphs and parametric plots of functions in two and three dimensions, and animating them; drawing charts and diagrams; APIs for linking it on an external program such as a database, or using in a programming language to use the computer algebra system
The first two steps of the Gram–Schmidt process. In mathematics, particularly linear algebra and numerical analysis, the Gram–Schmidt process or Gram-Schmidt algorithm is a way of finding a set of two or more vectors that are perpendicular to each other.
A small signal model consists of a small signal (having zero average value, for example a sinusoid, but any AC signal could be used) superimposed on a bias signal (or superimposed on a DC constant signal) such that the sum of the small signal plus the bias signal gives the total signal which is exactly equal to the original (large) signal to be ...
The internal state variables are the smallest possible subset of system variables that can represent the entire state of the system at any given time. [13] The minimum number of state variables required to represent a given system, , is usually equal to the order of the system's defining differential equation, but not necessarily.