Set up
  • Setting up an Integrated Development Environment (IDE)
  • Overview of CodeBlocks
  • Downloading gnuplot
  • Installing gnuplot
  • Overview of gnuplot
Getting started with gnuplot
  • Plotting signals with gnuplot
  • Plotting multiple signals in the same window
Signal Statistics and Noise
  • Nature of a signal
  • Mean and Standard Deviation
  • Signal-to-Noise ratio
  • Coding : Developing the Signal Mean algorithm
  • Coding : Computing the Signal Mean
  • Coding : Developing the Signal Variance algorithm
  • Coding : Developing the Signal Standard Deviation algorithm
Quantization and The Sampling Theorem
  • Quantization
  • Nyquist Theorem ( Sampling Theorem )
  • The Passive Low-Pass Filter
  • The Passive High-Pass Filter
  • The Modified Sallen-Key Filter
  • The Bessel, Chebyshev and Butterworth filters
  • Comparing the performance of the Bessel, Chebyshev and Butterworth filters
  • Information encoding : Time-domain and frequency-domain encoding
Linear Systems and Superposition
  • Notice
  • Signal naming conventions
  • System Homogeneity
  • System Additivity
  • System Shift Invariance
  • Synthesis and Decomposition
  • Impulse Decomposition
  • Step Decomposition
Convolution
  • Introduction to Convolution
  • The Delta Function and Impulse Response
  • The Convolution Kernel
  • The Convolution Kernel (Part II)
  • The Output side analysis and the convolution sum equation
  • Coding : Developing the Convolution algorithm (Part I )
  • Coding : Developing the Convolution algorithm (Part I I)
  • Coding : Developing the Convolution algorithm (Part III)
  • Coding : Developing the Convolution algorithm (Part IV)
  • The Identity property of convolution
  • The Running Sum and First Difference
  • Coding : Developing the Running Sum algorithm
Fourier Transsform
  • Introduction to Fourier Analysis
  • Introduction to Discrete Fourier Transform
  • DFT Basis Functions
  • Deducing the Inverse DFT
  • Calculating the Discrete Fourier Transform (DFT)
  • Code : Developing the DFT algorithm (Part I)
  • Code : Developing the DFT algorithm (Part II)
  • Code : Developing the DFT algorithm (Part III)
  • Coding : Developing the Inverse DFT algorithm (Part I)
  • Coding : Developing the Inverse DFT algorithm (Part II)
  • Coding : Developing the Inverse DFT algorithm (Part III)
  • Coding : Computing the DFT and IDFT of an ECG signal (Part I)
  • Coding : Computing the DFT and IDFT of an ECG signal (Part II)
  • Coding : Identifying the frequencies present in the DFT plot
  • Symmetry between Time domain and frequency domain -Duality
  • Polar Notation
  • Coding : Rectangular notation to the polar notation ( Part I)
  • Coding : Rectangular notation to the polar notation ( Part II)
  • Introduction to Spectral Analysis
  • The Frequency Response
Complex Numbers
  • The Complex Number System
  • Polar Representation of Complex Numbers
  • Euler's Relation
  • Representation of Sinusoids
  • Representing Systems
Complex Fourier Transform
  • Introduction to Complex Fourier Transform
  • Mathematical Equivalence
  • The Complex DFT Equation
  • Comparing Real DFT and Complex DFT
  • Coding : Developing the Complex DFT equation (Part I)
  • Coding : Developing the Complex DFT equation (Part II )
Fast Fourier Transform (FFT)
  • An Overview of how FFT works.
  • Understanding the complexity of calculating DFT directly
  • How the Decimation -in-Time FFT Algorithm works
Digital Filter Design
  • Introduction to Digital Filters
  • The Filter Kernel
  • The Impulse,Step and Frequency response
  • Understanding the Logarithmic scale and decibels
  • Information representations of a signal
  • Time domain parameters
  • Frequency domain parameters
  • Designing digital filters using the spectral inversion method
  • Designing digital filters using the spectral reversal method
  • Classification of digital filters
Designing Finite Impulse Response FIR) Filters
  • The Moving Average Filter
  • The Multiple Pass Moving Average Filter