Numerical methods for Computer Engineering

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KHUDKIBOOK
NUMERICAL METHODS FOR 2710210
FREE PDF 2710210
Code: 2710210 Credits: 4 Semester 1 CE(A

Numerical methods for Computer Engineering

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Numerical methods for Computer Engineering Syllabus — Unit-wise Content

The official GTU curriculum for Numerical methods for Computer Engineering (subject code 2710210) as prescribed for CE(A · Semester 1 divides the course into 7 units, covering 42 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (2710210)

Unit 1 Modeling, Computers and error analysis

6 lecture hours

  • Mathematical modeling and engineering problem solving
  • Role of computers and software
  • Approximations and errors
  • Significant figures
  • accuracy and precision
  • round-off and truncation errors
  • error propagation

Unit 2 Roots of Equations

6 lecture hours

  • Mathematical background
  • Regula Falsi
  • NR method
  • Successive approximation method
  • Budan’s Theorem
  • Barristow’s method
  • case studies

Unit 3 Systems of linear algebraic equations

6 lecture hours

  • Mathematical background
  • Gauss elimination
  • pitfalls and techniques for improvement
  • matrix inversion and Gauss-Seidel methods
  • III Conditional equations
  • Predictor-Corrector methods
  • case studies

Unit 4 Curve Fitting

4 lecture hours

  • Mathematical background
  • Least squares linear and polynomial regression
  • Lagrange interpolating polynomials
  • Spline interpolation
  • Case studies

Unit 5 Numerical Integration

  • Newton-Cotes integration formulas
  • trapezoidal rule and Simpson’s rules: Interpolation
  • case studies. 4 15

Unit 6 Ordinary differential equations

6 lecture hours

  • Euler’s method
  • Runge-Kutta methods
  • General methods for boundary value problems
  • Automatic error monitoring and change of step size stability of solution
  • Case studies

Unit 7 Statistical Methods

4 lecture hours

  • Frequency distributions
  • Data analysis
  • Expectations and moments
  • Co- relation and regression
  • Trend analysis
  • Seasonal effects
  • Cyclical fluctuation
  • Moving average, MSE, Predictions

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