Signal Processing
- Discrete Time Signal Processing
- Sampling Theorem: Continuous and Discrete time
- Interpolation and Up sampling
- Decimation and Down sampling
- ADC and DAC Convertors
- Overview of Transforms
- Convolution Operation
- IIR and FIR Filter Structures
- Pole-Zero Representations
- Fourier and Z Transforms
- Power Spectral Density (PSD)
- Linear Filtering
- Discrete Fourier Transforms (DFT)
- FFT and IFFT
- Probability Overview
- Mean, Variance, Several Theorems
- PDF Examples: Gaussian, Erlang, Exponential, Uniform, etc.
- Central Limit Theorem
- Hypothesis Testing (MAP, ML)
- Calculating Probability of Error
- Digital Communications Systems Example
- The importance of the PDF and CDF
- Linear Algebra Methods
- Dot Product and Cross Product
- Matrix Inversion
- Eigen Decomposition
- Adaptive Signal Processing
- Minimum Mean Square Error (MMSE)
- Least Mean Squared (LMS) and NLMS
- Recursive Least Squared (RLS)
- Direct Matrix Inversion (DMI)
- Maximum Likelihood Estimation (MLE)
- Interpolation Techniques (Lagrange, Linear)
- Equalization Methods
- Decision Feedback Equalization (DFE)
- Maximum Likelihood Sequence Equalizer (MLSE)
- Communications Applications
- DC Offset Estimation
- Automatic Frequency Correction (AFC)
- Channel Estimation
- Likelihood Ratio Testing
- Phase Noise
- Estimators
- Properties of Estimators
- Digital Communications Application (BER)
- Wrap-up
- Course Recap and Q/A
- Evaluations
