Engineering Mathematics for EEE BEE301
Course Code: BEE301
Credits: 03
CIE Marks: 50
SEE Marks: 50
Total Marks: 100
Exam Hours: 03
Total Hours of Pedagogy: 40H
Teaching Hours/Weeks: [L:T:P:S] 3:0:0:0
Importance of higher-order ordinary differential equations in Electrical & Electronics
Engineering applications.
Higher-order linear ODEs with constant coefficients – Inverse differential operator,
problems.Linear differential equations with variable Coefficients-Cauchy’s and Legendre’s
differential equations – Problems.
Applications: Application of linear differential equations to L-C circuit and L-C-R circuit.
Self-Study: Finding the solution by the method of undetermined coefficients and method of
variation of parameters.
Principles of least squares, Curve fitting by the method of least squares in the form y = a + bx, y = a + bx + c * x ^ 2 , and y = axb. Correlation, Co-efficient of correlation, Lines of regression, Angle between regression lines, standard error of estimate, rank correlation.
Self-study: Fitting of curves in the form y = a e^bx
Periodic functions, Dirchlet’s condition, conditions for a Fourier series expansion, Fourier series of functions with period 2π and with arbitrary period. Half rang Fourier series. Practical harmonic analysis.
Application to variation of periodic current:
Self-study: Typical waveforms, complex form of Fourier series
Infinite Fourier transforms: Definition, Fourier sine, and cosine transform. Inverse Fourier transforms Inverse Fourier cosine and sine transforms. Problems.
Z-transforms: Definition, Standard z-transforms, Damping, and shifting rules, Problems. Inverse z-transform and applications to solve difference equations
Self-study: Convolution theorems of Fourier and z-transforms
Review of basic probability theory, Random variables-discrete and continuous Probability distribution function, cumulative distribution function, Mathematical Expectation, mean and variance, Binomial, Poisson, Exponential and Normal distribution (without proofs for mean and SD) – Problems.
Sampling Theory: Introduction to sampling distributions, standard error, Type-I and Type-II errors. Student’s t-distribution, Chi-square distribution as a test of goodness of fit.
Self-study: Test of hypothesis for means, single proportions only.