## Multiple Equation Solver

The **equation is a mathematical** tie, containing one or more variables. Solving the equation consists in finding the values of variables for which equality would be fulfilled. Variables are also called unknown, values for which equality is satisfied-solutions of the equation. Unlike the identity, the equation is a draw, which is not necessarily to be performed for all possible values of the variable.

There are a variety of equations that are used in various areas of mathematics, such as the methods of their solution differ, depending on the type of equation.

Multiple Equation Solver In the algebra are dealt with two main groups of equations solver and linear equations systems. Polinomnite equations have a common type of P (X) = 0, where P is a polynomial function, and the systems of linear equations-a (x) + b = 0, where a linear image and b and the unknown x are vectors. For solving algebraic equations using algorithmic or geometric methods based on linear algebra or calculus.

Explore algebra and Diophantine equations where the coefficients and the solutions are integers, as they use different methods, based on the arithmetic. These equations are usually difficult and most often they are looking for whether there are only solutions and what is their number.

In geometry, Multiple Equation Solver used to describe the different geometric objects. Here the goal is not finding solutions, and the demonstration and testing of certain geometrical properties. In this area are two large groups of equations-Cartesian and parametric.

Explore calculus equations of the type f (x) = 0, where f is a function with certain properties, such as continuity. The methods of solving these equations allow for the construction of the series of decisions, the goal is to reach the right decision as soon as possible.

Dynamic systems are defined by equations whose solutions are ranks or functions of one or more variables. In this context, be considered two main issues — the initial state and the asymptotic behavior. For each acceptable, for example, the value of the sequence or function at zero, the equation allows certain single solution. Sensitivity of decisions to small changes in the initial state is one of the main tasks. Asymptotic behavior of a solution is the form of the solution in the values of the variable, tending to infinity. If the decision is not razhodâŝo, it may converge to a value, there are cyclical or erratic behavior.

It was later removed and the main theorem of algebra that any polynomial equation of degree greater than zero and with real or complex coefficients has at least one complex root. Although this theorem guarantees the existence of solution for a very broad range polynomial equations, it does offer a solution, obviously the presence of complex roots of equations with real coefficients is not intuitively obvious. The theorem of Abel-Rufini gives an explanation of this fact, by showing that for polinomnite equations of higher degree does not exist a common formula, similar to those for the equations to the fourth degree. This conclusion, which reaches to Niels Henrik Abel, is complemented by Évariste Galois, who displays a necessary and sufficient condition for existence of solution of a similar type of equations. In the history of mathematics, basic theorem of algebra and theorem of Abel-Rufini form popular in the 19th century, the theory of equations, which today is not regarded as an autonomous field of mathematics.

The geometry allows for the creation of more efficient algorithms for solving linear equations. The scheme shows a three dimensional image of the function f.

Scheme of the wall brackets on the function f and the red green show segment road approximately solution that is performed with two iterations in the two-dimensional case.

The geometric interpretation of systems of linear equations gives additional information about their character. The image of Multiple Equation Solver the linear operator form a vector subspace, similar to the plane in three-dimensional space. The core of a (vectors of multiple, whose image is the zero vector) is also subspace. These results indicate that solution forms a space.

With the increase of the degree of equation solution becomes more complicated. Even the **equation of second degree** is not just in the General case (see for example Fermat’s Theorem or Euler’s equation Pell). Through the use of specially created for this purpose, methods and assumptions, such as the method of infinite descent and the small Farm theorem, it is possible to solve some private cases.

The general solution of the *equation of second degree* requires the use of more sophisticated methods, such as those of algebraic number theory. Need more detailed notions of number sets and research of terminal boxes and whole algebraic numbers with the help of the theory of Galois. So while the decision of the algebraic equation of the second degree is found from Horezmi back in the 8th century, the equation is resolved only at the end of the 19th century by David Hilbert. The analysis of the Diophantine equations is often so complex that is limited to the determination of existence of solutions and their number.

Diophantine equations are widely used in the field. Tools, based on their analysis, capable of detecting and correcting errors and are at the heart of the algorithms. At the root of many ciphers stand Diophantine equations that describe simple but whose solution requires practically unattainable processing time. For example, the equation n = x. y, where n is a fixed natural number, and x and y are unknown, cannot be decided practically, if n is the product of two sufficiently large primes.