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DIGITAL SIGNAL PROCESSING
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Unit - I
Introduction
Signals, Systems and Signal Processing, Classification of Signals, The Concept of Frequency in Continuous-Time and Discrete -Time Signals, Analog-to-Digital and Digital-to-Analog Conversion
Discrete-Time Signals and Systems
Discrete-Time Signals, Discrete-Time Systems, Analysis of Discrete-Time Linear Time-Invariant Systems,Discrete-Time Systems Described by Difference Equations, Implementation of Discrete-Time System 2.6 Correlation of Discrete-Time Signals
The Z-Transform Abd its Application to the Analysis of Lti Systems
The z- transform, Properties of the z- Transform , Rational z- Transforms , Inversion of the z- Transform , Analysis of Linear Time Invariant Systems in the Z-domain, The One-Sided z-Transform
Unit -II
Frequency Analysis of Signals and Systems
Frequency Analysis of Continuous-Time Signals, Frequency Analysis of Discrete- Time Signals, Frequency-Domain and Time-Domain Signal Properties, Properties of the Fourier Transform for Discrete-Time Signals
Sampling and Reconstruction of Signals
Ideal Sampling and Reconstruction of Continuous-Time Signals, Discrete-Time Processing of Continuous-Time Signals, Analo-to-Digital and Digital-to_Analog Converters, Sampling and Reconstruction of Continuous -Time Bandpass Signals, Sampling of Discrete-Ti
The Discrete Fourier Transform : Its Properties And Applications
Frequency Domain Sampling: The Discrete Fourier Transform, Properties of the DFT, Linear Filtering Methods Based on the DFT, Frequency Analysis of Signals Using the DFT, The Discrete Cosine Transform
Unit - III
Efficient Computationof the Dft : Fast Fourier Transform Algorithms
Efficient Computation of the DFT:FFT Algorithms , Applications of FFT Algorithms, A Linear Filtering Approach to Computation of the DFT, Quantization Effects in the Computation of the DFT
Multirate Digital Signal Processing
Introduction, Decimation by a Factor D, Interpolation by a Factor I, Sampling Rate Conversion by a Rational Factor I/D, Implementation of Sampling Rate Conversion, Multistage Implementation of Sampling Rate Conversion, Sampling Rate Conversion of Band PAs
Unit - IV
Linear Prediction and Optimum Linear Filters
Random Signals, Correlation Functions and Power Spectra, Innovations Representation of Stationary Random Process , Forward and Backward Linear Prediction, Solution of the Normal Equations, Properties of the Linear Prediction- Error Filters , AR Lattice an
Adaptive Filters
Applications of Adaptive Filters, Adaptive Direct- form Filters- The LMS Algorithm, Adaptive Direct-Form FIR Filters-RLS Algorithms, Adaptive Lattice-Ladder Filters
Power Spectrum Estimation
Estimation of Spectra from Finite -Duration Observations of Signals, Non Parametric Methods for Power Spectrum Estimation, Parametric Methods for spectrum Estimation, Filter Bank Methods, Eigenanalysis Algorithms for Spectrum Estimation
Computer Science
Engineering
IInd Semester
Yearbook
Bapatla Engineering College
Acharya Nagarjuna University
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