# Non-Linear Transcendental and Polynomial Function Techniques | Numerical Methods Lesson 2

Non-linear, transcendental, and polynomial functions are important classes of mathematical functions that are commonly used in a variety of fields, including engineering, physics, and economics.

1. Non-linear Functions: Non-linear functions are functions that do not have a linear relationship between the input and output variables. Examples of non-linear functions include exponential functions, logarithmic functions, and trigonometric functions. Non-linear functions are often used to model complex systems or relationships.
2. Transcendental Functions: Transcendental functions are functions that are not algebraic. They cannot be expressed as a finite combination of algebraic functions, including polynomials and rational functions. Examples of transcendental functions include exponential functions, logarithmic functions, trigonometric functions, and inverse trigonometric functions.
3. Polynomial Functions: Polynomial functions are functions that can be expressed as a finite sum of powers of the variable, with coefficients that are constants. For example, the function f(x) = 3x^2 – 2x + 1 is a polynomial function of degree 2. Polynomial functions are important in many areas of mathematics, including calculus, algebra, and number theory.

Techniques for working with non-linear, transcendental, and polynomial functions include:

1. Root-finding methods: These techniques are used to find the roots, or zeros, of a function. Examples of root-finding methods include the bisection method, the Newton-Raphson method, and the secant method.
2. Curve fitting: Curve fitting techniques are used to find a function that best fits a given set of data points. Examples of curve fitting techniques include polynomial regression, spline interpolation, and nonlinear regression.
3. Optimization methods: These techniques are used to find the maximum or minimum value of a function. Examples of optimization methods include the simplex method, gradient descent, and simulated annealing.
4. Numerical integration: Numerical integration techniques are used to approximate the value of an integral of a function. Examples of numerical integration techniques include the trapezoidal rule, Simpson’s rule, and Monte Carlo integration.

## Non-Linear Function

Nonlinear functions are mathematical functions that do not have a linear relationship between the input and output variables. In other words, the rate of change of the output variable is not constant with respect to the input variable, unlike linear functions where the rate of change is constant. Nonlinear functions are commonly used to model complex systems or relationships that cannot be easily explained by linear relationships.

Examples of nonlinear functions include exponential functions, logarithmic functions, trigonometric functions, and polynomial functions of degree higher than one. These functions have a wide range of applications in fields such as physics, engineering, economics, and biology.

Exponential functions are nonlinear functions that have the form f(x) = a^x, where a is a constant greater than 1. Exponential functions are used to model growth and decay processes, such as population growth or radioactive decay. The rate of change of an exponential function is proportional to the function itself, which results in exponential growth or decay.

Logarithmic functions are another example of nonlinear functions, which have the form f(x) = log_a(x), where a is a constant greater than 1. Logarithmic functions are the inverse of exponential functions and are used to solve exponential equations. Logarithmic functions are also used to represent orders of magnitude, such as in the Richter scale used to measure earthquake intensity.

Trigonometric functions such as sine, cosine, and tangent are also nonlinear functions. These functions are used to model periodic phenomena such as sound waves or electromagnetic waves.

Polynomial functions of degree higher than one, such as quadratic functions (f(x) = ax^2 + bx + c) or cubic functions (f(x) = ax^3 + bx^2 + cx + d), are also nonlinear functions. These functions are used to model a wide range of physical and biological phenomena, such as motion or chemical reactions.

Working with nonlinear functions often requires specialized techniques such as numerical methods, root-finding methods, and optimization methods. These techniques are used to solve nonlinear equations, find the maximum or minimum value of a function, or approximate the solution to a differential equation. The study of nonlinear functions is a rich and fascinating field of mathematics with many important applications in science, engineering, and economics.

Example

Example: f(x) = x^2

Explanation: This is a non-linear function because the rate of change of the function is not constant. When x increases by 1, the value of f(x) increases by 2x + 1. For example, when x = 1, f(x) = 1^2 = 1, and when x = 2, f(x) = 2^2 = 4. The difference between these values is 3, which is not constant.

Proving that a function is non-linear

The following are ways to prove that an equation is non-linear:

1. Identify the variables: Look at the equation and identify the variables. If the equation contains variables that are raised to a power other than 1, such as x^2, x^3, or higher, then the equation is likely to be non-linear.
2. Check for constant rates of change: For a linear equation, the rate of change of the dependent variable with respect to the independent variable is constant. This means that if x increases by a certain amount, then the value of y also increases by a constant amount. For a non-linear equation, the rate of change is not constant.
3. Use differentiation: Another way to determine if an equation is non-linear is to take its derivative. If the derivative of the equation contains any terms that are not linear (i.e., contain variables raised to powers other than 1), then the equation is non-linear.
4. Plot the function: Graph the function using software or by hand to see if the curve is a straight line or a curved line. If the curve is a straight line, then the function is linear. If the curve is not a straight line, then the function is non-linear.
5. Look for higher-order terms: In addition to the variables raised to powers other than 1, look for other higher-order terms in the equation, such as square roots or trigonometric functions. These terms can also make an equation non-linear.

## Transcendental Functions

Transcendental functions are functions that are not algebraic, meaning they cannot be expressed as finite combinations of addition, subtraction, multiplication, division, and the extraction of roots. Here are some examples of transcendental functions:

1. Exponential function: f(x) = e^x, where e is the mathematical constant approximately equal to 2.71828.
2. Logarithmic function: f(x) = log_a(x), where a is a constant greater than 0 and not equal to 1.
3. Trigonometric functions: sine, cosine, tangent, cotangent, secant, and cosecant functions.
4. Inverse trigonometric functions: arcsine, arccosine, arctangent, arccotangent, arcsecant, and arccosecant functions.
5. Hyperbolic functions: sinh, cosh, tanh, coth, sech, and csch functions.
6. Special functions: gamma, beta, Bessel, Legendre, and elliptic functions.

## Polynomial Functions

A polynomial function is a function that can be expressed as a polynomial, which is a finite sum of terms that each consist of a variable raised to a non-negative integer power, multiplied by a constant coefficient. Here is an example of a polynomial function:

In this function, the highest power of the variable x is 4, which is the degree of the polynomial. Here are some properties of polynomial functions:

1. Polynomial functions are continuous and differentiable over their domains.
2. The degree of a polynomial function determines its end behavior: if the degree is even, the ends of the graph point up; if the degree is odd, the ends of the graph point down.
3. The number of roots (solutions) of a polynomial equation is equal to its degree. For example, a fourth-degree polynomial can have up to four roots.
4. The Fundamental Theorem of Algebra states that every polynomial equation of degree n has exactly n complex roots (counting multiplicities).
5. Polynomials can be factored into linear and irreducible quadratic factors. This factoring can be useful in finding the roots of the polynomial, as well as in understanding its behavior.

## Subtopics

Non-Linear Transcendental and Polynomial Function Techniques are a group of mathematical methods used to solve complex equations that involve non-linear functions, transcendental functions, and polynomial functions. Here are some of the commonly used techniques:

1. Newton-Raphson method: A numerical method used to find the roots of a function, which involves using an initial guess and then iteratively refining it until the desired accuracy is achieved.
2. Bisection method: Another numerical method used to find the roots of a function, which involves narrowing down the interval containing the root by repeatedly dividing it in half.
3. Secant method: A numerical method used to find the roots of a function, which involves using two initial guesses and then iteratively refining them until the desired accuracy is achieved.
4. Regula falsi method: Another numerical method used to find the roots of a function, which is similar to the bisection method but uses a linear interpolation to narrow down the interval containing the root.
5. Fixed-point iteration: A numerical method used to find the fixed points of a function, which involves repeatedly applying the function to an initial guess until the result no longer changes.
6. Homotopy continuation method: A numerical method used to solve systems of polynomial equations by continuously deforming them into simpler ones that are easier to solve.
7. Differential transformation method: A mathematical technique used to transform differential equations into algebraic equations, which can then be solved using other methods.
8. Adomian decomposition method: A mathematical technique used to solve non-linear differential equations by decomposing them into simpler equations and then solving them iteratively.
9. Galerkin method: A numerical method used to solve partial differential equations by approximating the solution using a finite set of functions.