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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
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IInd Semester
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Bapatla Engineering College
Acharya Nagarjuna University
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