1- Knowledge and understandingGoal of the course is to provide the students with the basics of the analysis of discrete-time signals, the design of digital signal processing systems and digital filtering, of error control coding schemes, and their use in digital systems and communications.2- Applying knowledge and understandingStudents learn how to analyze and design simple linear systems (digital filters), error control schemes, and digital communication systems, being aware of the capabilities and practical limitations of digital signal processing techniques.
- Discrete-time signals and systems (4 hours)Basic discrete-time signals: unit impulse, unit step, real and complex exponential, periodic sequences. Discrete-time systems: memoryless, linear, time-invariant, causal, stable. Linear and time-invariant (LTI) systems and impulse response. Discrete convolution and properties of LTI systems. Difference equations.- Discrete-time Fourier transform (DTFT) (4 hours)Representation of sequences in the frequency domain. Frequency response. Representation of sequences through the Fourier transform. Definition and properties of the DTFT.- The z-Transform (6 hours)Definition and properties. Region of convergence and relationship between the z-transform and a system's properties. Inverse z-Transform. Transfer function of a LTI system.- Sampling of continuous-time signals (4 hours)Periodic sampling and frequency domain representation of sampled signals. The sampling theorem. Reconstruction of a signal from its samples. Discrete-time processing of continuous-time signals. Impulse invariance.- Analysis and representation of LTI systems (4 hours)Frequency response of LTI systems. System function. Representation of linear constant coefficients difference equations. Direct form I and II.- Discrete Fourier Transform (DFT) (8 hours)Discrete Fourier series and its properties. Periodic convolution. Sampling of the DTFT. DFT: definition and properties. Circular convolution. Use of the DFT in the implementation of LTI systems. Algorithms for the computation of the DFT. FFT algorithms and their complexity.- Digital filter design (6 hours)Definitions of the specifications of a filter. Design of IIR digital filters. Design of FIR filters.- Schemes for error detection and correction (9 hours)Schemes for automatic repeat request (ARQ). Schemes for forward error correction (FEC). Repetition codes. Parity check codes. Coding gain and cost. Bit interleaving. Code vectors and Hamming distance. Error control properties of a given code. Code rate and redundancy. Performance analysis of FEC systems. ARQ retransmission procedures. Performance analysis of ARQ systems. Outline of hybrid ARQ systems.- Block codes (7 hours)Linear systematic block codes. Matrix representation of a linear block code. Hamming codes. Maximum likelihood syndrom decoding. Example decoding of a Hamming (7,4) code. Cyclic codes. Cyclic shifts and code polynomials. Generator polynomial of a cyclic code. Systematic codes. Coding and decoding as the remainder of polynomial divisions. Example of a Hamming (7,4) code. Circuit implementation of encoders and decoders for cyclic codes. Outline of BCH and CRC codes. Outline of M-ary and Reed-Solomon codes.- Convolutional codes (7 hours)Tree, trellis and state diagrams of convolutional codes. Gnerator polynomials. Free distance. Transfer function and weight distribution of a convolutional code. Estimation of error probability. Coding gain. Decoding of convolutional codes. Viterbi decoding. Sequential decoding. Outline of majority logic decoding. Outline of punctured codes. Soft-decision decoding. Examples of convolutional codes and their performance.- Further topics (1 hour)Punctured codes. Concatenated codes. Convolutional codes with feedback (recursive). Outline of turbo codes.
discrete time signal processing oppenheim solutions 3rd edition.zip
This paper proposes a solution to the sampled-data regulation problem for feedback linearizable n-link robotic manipulators. The prime focus is on the development and stability analysis of the proposed control scheme in the presence of model uncertainties and external disturbances. A major constraint is the availability of sampled measurements of output signal. This leads to designing an impulsive observer for feedback linearization. The discrete-time control input is mapped into its continuous-time counterpart using a realizable reconstruction filter (RRF). The underlying control scheme relies on the sampled-data regulator theory based on the discrete-time equivalence of the plant and RRF modeled as impulsive system. This method leads to controller/observer design in discrete time. The working of the entire scheme is dependent on the stability of impulsive observer; hence a Lyapunov-based stability analysis is also included to ensure the stability of a closed-loop system. The working of the proposed scheme along with a comparison with conventional solution is presented, when applied to the control of a 3-degree-of-freedom PUMA 560 robot.
The students will be able to apply methods and techniques from audio signal processing in the fields of mobile and internet communication. They can rely on elementary algorithms of audio signal processing in form of Matlab code and interactive JAVA applets. They can study parameter modifications and evaluate the influence on human perception and technical applications in a variety of applications beyond audio signal processing. Students can perform measurements in time and frequency domain in order to give objective and subjective quality measures with respect to the methods and applications. 2ff7e9595c
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