KERALA TECHNOLOGICAL UNIVERSITY
KERALA TECHNOLOGICALUNIVERSITY(THRISSUR CLUSTER - 07)SCHEME AND SYLLABIofM. TECH.inCOMMUNICATION ENGINEERING &SIGNAL PROCESSINGOFFERING DEPARTMENTELECTRONICS & COMMUNICATIONENGINEERING1
CLUSTER LEVEL GRADUATE PROGRAM COMMITTEE1.Dr Devdas Menon, Professor, IIT Madras, Chennai2Principal, Government Engineering College Trichur, Thrissur Convener3Principal, AXIS College of Engineering & Technology, EastKodaly, Murikkingal, ThrissurMember4Principal, IES College of Engineering, Chittilappilly,ThrissurMember5Principal, MET'S School of Engineering, Mala, ThrissurMember6Principal, Royal College of Engineering & Technology,Akkikkavu, ThrissurMember7Principal, Vidya Academy of Science & Technology,Thalakkottukara, ThrissurMember8Principal, Thejus Engineering College, Vellarakkad,Erumappetty, ThrissurMember9Principal, Universal Engineering College, Vallivattom,Konathakunnu, ThrissurMember10Principal, Sahrdaya College of Engineering & Technology,Kodakara, ThrissurMember2Chairman
CERTIFICATEThis is to certify that1. The scheme and syllabi are prepared in accordance with the regulation andguidelines issued by the KTU from time to time and also as per the decisionsmade in the CGPC meetings.2. The suggestions/modifications suggested while presenting the scheme and syllabibefore CGPC on 25.6.2015 have been incorporated.3. There is no discrepancy among the soft copy in MS word format, PDF and hardcopy of the syllabi submitted to the CGPC.4. The document has been verified by all the constituent colleges.Coordinator in charge of syllabus revision of the programme(Name, designation and College Name)Principal of the lead college(Name and Name of the College)Principals of the colleges in which the programme is offeredName of the collegePrincipal’s NameGovernment EngineeringCollege Trichur, ThrissurDr. K P IndiradeviDate:Place:SignatureChairman3
VISION and MISSION of the ProgrammeVISIONTo achieve academic excellence through quality education in theintertwined fields of Communication Engineering and SignalProcessingMISSIONTo impart quality education by providing excellent learning andresearch environment, enabling the students to apply signalprocessing techniques innovatively to address the challenges in therapidly growing field of communication engineering for the benefitof humanity.4
PROGRAM EDUCATIONAL OBJECTIVES(PEOs)a. To meet the requirements of talented Research and Developmentprofessionals solving real-life problems arising in the field ofElectronics, Communication Engineering and Signal Processing.b. To meet the requirements of faculty with specialization inCommunication Engineering and Signal Processing in academicinstitutions.c. To cater to the needs of engineering professionals in SignalProcessing / Communication related IT sectors.d. To foster the students’ ability to think differently so that they developinto entrepreneurs, opening their own business enterprises.e. To train our students to meet the requirements in the modern multidisciplinary research scenario which is a blend of many conventionaldisciplines including Electronics, Mathematics, Biology, Optics,Mechanics and Medicine5
PROGRAM OUTCOMES (POs)At the end of the course the student should be able toA. Apply the knowledge gained from advanced Mathematics andEngineering courses to research problems in CommunicationEngineering and Signal Processing.B. Design, Conduct or Simulate experiments in areas related toCommunication Engineering and Signal Processing and criticallyanalyze the results.C. Design/Model Signal Processing algorithms/systems for ductperformance evaluation and comparison with the results reportedin literature.D. Function effectively in groups to undertake projects ininterdisciplinary areas.E. Perform identification and formulation of open research problemsin the field of Communication Engineering in pursuance ofpossible solutions.F. Understand icalG. Communicate effectively with the technical community anddisseminate the knowledge acquired to the benefit of society.H. Understand the impacts of technical solutions to engineeringproblems on the society.6
I. Recognize the importance and need for an active and co-operativelifelong-learning attitude.J. Understand the prevailing professional and societal issues.K. Develop skills to apply modern engineering tools and techniques.7
Scheme of M‐Tech programme in Communication Engineering &Signal ProcessingSemester IExamSlotCourse No:A07MA6013BCDENameHours/WeekInternalMarksEnd Semester ExamCreditsMarksDuration(hrs)4060340 040603440 0406034Advanced DigitalSignal Processing30 0406033Elective I30 0406033ResearchMethodology02 010000207EC6211AdvancedCommunicationEngineering Lab00 210000107EC6213Introduction to0 0 1seminarTOTAL 18 2 340030007EC620307EC620507EC620707EC62X907GN6001LT P40 04Information TheoryMathematics forCommunicationEngineeringAdvanced DigitalCommunication821
Semester meLTPInternalMarks400303Elective IIEnd Semester 300406033Elective III300406033Seminar002100002Mini Project0041000020021000018500300Estimation andDetectionWirelessCommunicationReal Time DigitalSignal ProcessingSignal ProcessingLabTOTAL16921
Semester 7207Hours/WeekEnd Semester ExamDurationMarks(hrs)LTPInternalMarksElective IV300406033Elective ject(Phase 1)TOTAL6Credits14Semester alMarksProject(Phase 2)002170End Semester ExamDurationMarks(hrs)30L – Lecture, T – Tutorial, P – PracticalTotal number of credits for the PG Programme: 21 21 14 12 6810Credits12
LIST OF ELECTIVE COURSES OFFEREDSemester IElective I1. 07EC6209 Optimization Techniques2. 07EC6219 Markov Modeling and Queuing Theory3. 07EC6229 Digital Image Processing4. 07EC6239 Biomedical Signal Processing5. 07EC6249 R F System DesignSemester IIElective II1. 07EC6228 Multirate Signal Processing2. 07EC6238 Adaptive Signal Processing3. 07EC6248 Advanced Optical Communication4. 07EC6258 Antenna theory and Design5. 07EC6268 Multidimensional Signal ProcessingElective III6. 07EC6222 Wavelets Theory and Applications7. 07EC6232 Coding theory8. 07EC6242 Communication Networks9. 07EC6252 Computational Electromagnetics10. 07EC6262 High Speed Digital Systems11. 07EC6272 Spectrum Analysis of Signals11
Semester IIIElective IV1. 07EC7201 Transform Theory2. 07EC7211 Wireless sensor networks3. 07EC7221 Pattern recognition and Machine learning4. 07EC7231 Speech and Audio Signal Processing5. 07EC7241 Secure CommunicationElective V6. 07EC7203 Cognitive and Software Defined Radio7. 07EC7213Embedded System Design8. 07EC7223Multimedia Compression Techniques9. 07EC7233Linear System Theory10. 07EC7243 Compressed Sampling: Principles and Algorithms12
SYLLABI13
Semester ICore Courses07MA 6013 MATHEMATICS FOR COMMUNICATIONENGINEERINGCredits: 4-0-0: 4Year :2015Prerequisite: Matrix theory and Probability theoryCourse objectives To provide necessary basic concepts in statistical signal analysis. To study random processes and its properties To have an idea of vector spacesSyllabusOperations on random variables, Distributions, Density functions, Moment generatingfunction, Conditional Expectation, Transformation of Random Variables, Classificationof general stochastic processes, Review of basics of linear algebra: Rank, Solutions ofEquations, Gram‐ Schmidt Orthogonalization Procedure, Linear transformations, Matrixrepresentation, Eigen values and Eigen vectors of linear operator, Random Processes,Markov Chains, Basic limit theorem, Continuous Time Markov Chains, Birth and deathprocesses, Finite state continuous time Markov chains, Second Order StochasticProcesses, Wide sense Stationary processes, Spectral density function, Low pass andband pass processes, White noise integrals, Linear Predictions and Filtering, Applicationsin Signal Processing and Communication: (To be engaged by a faculty from the ECEDept. in 2/3 hours)Course outcomes Have a good knowledge of standard distributions which can describe real lifephenomena. Acquire skills in handling situations involving several random variables andfunctions of random variables Better appreciation on the concepts of vector spaces14
References1. Kenneth Hoffman and Ray Kunze, Linear Algebra, 2nd Edition, PHI.2. Erwin Kreyszig, Introductory Functional Analysis with Applications, JohnWiley& Sons.3. Irwin Miller and Marylees Miller, John E. Freund’s Mathematical Statistics, 6thEdition, PHI.4. S. Karlin & H.M Taylor, A First Course in Stochastic Processes, 2nd edition,Academic Press, New York.5. S. M. Ross, Introduction to Probability Models, Harcourt Asia Pvt. Ltd. AndAcademic Press.6. J. Medhi, Stochastic Processes, New Age International, New Delhi.7. A Papoulis, Probability, Random Variables and Stochastic Processes, 3rdEdition,McGraw Hill.8. John B Thomas, An Introduction to Applied Probability and RandomProcesses,John Wiley & Sons.15
COURSE PLAN07MA 6013MATHEMATICS FOR COMMUNICATION ENGINEERING(L-T-P : 4-0-0) CREDITS:4MODULESContact Sem.ExamhoursMarks;%Module 1: Operations on random variables: Random Variables,Distributions and Density functions, Moments and Momentgenerating function, Multivariate distributions, IndependentRandom Variables, Marginal and Conditional distributions.Module 2: Conditional Expectation, Transformation of RandomVariables, elements of stochastic processes, Classification ofgeneral stochastic processes.FIRST INTERNAL TESTModule 3: Review of basics of linear algebra: Rank, Solutions ofEquationsLinear Algebra: Vector spaces, subspaces, Linear dependence,Basis and Dimension, Inner product spaces, Gram‐ SchmidtOrthogonalization ProcedureModule 4: Linear transformations, Kernels and Images, Matrixrepresentation of linear transformation, Change of basis, Eigenvalues and Eigen vectors of linear operator, Quadratic form.SECOND INTERNAL TESTModule 5: Random Processes: Markov Chains‐ Definition,Examples, Transition Probability Matrices of a Markov Chain,Classification of states and chains, Basic limit theorem, Limitingdistribution of Markov chains. Continuous Time Markov Chains:General pure Birth processes and Poisson processes, Birth anddeath processes, Finite state continuous time Markov chainsModule 6: Second Order Processes: Second Order StochasticProcesses, Linear operations and second order calculus, Stationaryprocesses, Wide sense Stationary processes, Spectral densityfunction, Low pass and band pass processes, White noise andwhite noise integrals, Linear Predictions and Filtering.Applications in Signal Processing and Communication: (To beengaged by a faculty from the ECE Dept. in 2/3 hours)Internal Assessment:40 MarksAssessment procedurei)Two internal tests, each having 15%ii)Tutorials/Assignments/ Mini projects having 10%iii)End Semester examination having 60%1691591591591510201020
07EC 6203 ADVANCED DIGITAL COMMUNICATIONCredits: 4-0-0: 4Year :2015Prerequisite: Digital Communication at the under graduate levelCourse Objectives To introduce various digital modulation schemes and channel models. To address the issues related with the recent developments in the area of ModernCommunication. To evaluate the performance of the systems and study the application.SyllabusReview of Random Variables and Processes, Characterization of CommunicationSignals and Systems, Signal space representation, Optimum waveform receiver inadditive white Gaussian noise (AWGN) channels, Correlation receiver, Matched filterreceiver and error probabilities, Optimum Receiver for Signals with random phase inAWGN Channels, Probability of error for envelope detection, Digital Communicationover Fading Channels, Optimum noncoherent receiver in random amplitude randomphase channels, Performance of digital Modulation schemes, Communication over bandlimited channels, Optimum pulse shaping, Equalization Techniques.Course outcomes Understand the design issues of Digital Communication over Additive GaussianNoise Channels, over Band limited Channels and Fading Multipath Channels Better appreciation of various digital communication receivers, equalizationtechniques etc.References1. J.G. Proakis, Digital Communication, MGH 4th edition.2. Edward. A. Lee and David. G. Messerschmitt, Digital Communication, AlliedPublishers (second edition).3. Marvin.K.Simon, Sami. M. Hinedi and William. C. Lindsey, DigitalCommunication Techniques, PHI4. William Feller, An introduction to Probability Theory and its applications, Wiley5. Sheldon.M.Ross, Introduction to Probability Models, Academic Press, 7th edition17
COURSE PLAN07EC 6203 ADVANCED DIGITAL COMMUNICATION(L-T-P : 4-0-0) CREDITS:4MODULESContact Sem. ExamhoursMarks;%Module 1: Review of Random Processes: Moment generatingfunction, Chernoff bound, Markov’s inequality, Chebyshev’s915inequality, Central limit Theorem, Chi square, Rayleigh andRician distributions, Correlation, Covariance matrix,Module 2: Stationary processes, wide sense stationaryprocesses, ergodic process, crosscorrelation and autocorrelationfunctions, Gaussian processes Communication over Additive1015Gaussian Noise Channels, Characterization of CommunicationSignals and Systems: Signal space representation ‐Overview,Signal detection in Gaussian channels.FIRST INTERNAL TESTModule 3: Optimum receiver in additive white Gaussian noise(AWGN) channels, Cross correlation receiver, Matched filterreceiver and error probabilities. Optimum Receiver for Signalswith random phase in AWGN Channels, Optimum receiver for1015Binary Signals, Optimum receiver for M‐ary Orthogonalsignals, Probability of error for envelope detection of M‐aryOrthogonal signalsModule 4: Digital Communication over Fading Channels:Characterization of Fading Multipath Channels, Rayleigh andRician Fading channels, Optimum non coherent receiver in915random amplitude random phase channels, performance inRayleigh and Rician channels,SECOND INTERNAL TESTModule 5: Performance of digital Modulation schemes such asBPSK, QPSK, FSK, DPSK etc over wireless channels,920Communication over bandlimited channels: Optimum pulseshapingModule 6: Equalization Techniques- Zero forcing linearEqualization- Decision feedback equalization- Adaptive920Equalization- Receiver synchronization: Frequency and phasesynchronization-symbol synchronizations.Internal Assessment:40 MarksAssessment procedurei)Two internal tests, each having 15%ii)Tutorials/Assignments/ Mini projects having 10%iii)End Semester examination having 60%18
. 07EC 6205 INFORMATION THEORYCredits: 4-0-0: 4Year :2015Prerequisite: A first course in Probability Theory and Random ProcessesCourse Objectives To provide a deep understanding of Information and its measurementTo familiarize the students with the various Source coding schemesTo impart the students the concept of Channel capacity for both discrete andcontinuous channels and Shannon’s theorems.To give the knowledge of Rate distortion theory and its applicationsSyllabusRepresentation of discrete sources, Entropy, Lossless source coding, Uniquely decodablecodes, Optimal codes, Huffman code, Shannon's Source Coding Theorem, Discretechannels, Channel Capacity, Arimoto- Blahut algorithm, Shannon's Channel CodingTheorem, Modeling of continuous sources and channels, Differential Entropy, Mutualinformation, Mutual information and Capacity calculation for Band limited Gaussianchannels, Shannon limit-Introduction to Rate Distortion TheoryCourse Outcomes Deep understanding of Information and its measurement Familiarization of various source coding schemes Familiarization of the concept of Channel capacity for both discrete and continuouschannels and Shannon’s theorems Thorough understanding of Rate distortion theory and its applicationsReferences:1. T. Cover and Thomas, Elements of Information Theory, John Wiley & Sons2. Robert Gallager, Information Theory and Reliable Communication, John Wiley &Sons.3. R. J. McEliece, The theory of information & coding, Addison Wesley PublishingCo.4. T. Bergu, Rate Distortion Theory a Mathematical Basis for Data CompressionPH Inc.5. Special Issue on Rate Distortion Theory, IEEE Signal Processing Magazine,November 1998.19
COURSE PLAN07EC 6205 INFORMATION THEORY(L-T-P : 4-0-0) CREDITS:4MODULESContacthoursModule 1: Information and Sources:Definition ofinformation-Zero Memory sources- Concepts of entropyLogarithmic inequalities-Properties of entropy-Extension of a9Zero memory source-Markov information sources- Entropycalculation- Entropy of a discrete Random variable- Joint,conditional and relative entropyModule 2: Properties of Codes: Uniquely decodable codesInstantaneous -codes- Construction of an instantaneous code 9Kraft’s inequality- Discussion, Statement and Proof–McMillan’s inequalityFIRST INTERNAL TESTModule 3: Coding Information Sources: Average length of acode -Optimal codes: Shannon codes- Fano codes -HuffmanCoding –Optimality of Huffman Codes- r-ary compact codes9Code efficiency and Redundancy- - Shannon’s source codingtheorem– Lempel Ziv codes -Arithmetic codingModule 4: Channels and Mutual Information: Informationchannel- Probability relations in a channel- A priori and Aposteriori entropies-Generalization ofShannon’s First9theorem-Mutual information- Properties of mutual informationNoiseless channels and deterministic channels-Cascadedchannels-Reduced channels and sufficient reductions.SECOND INTERNAL TESTModule 5: Channel Capacity: - Definition of Channelcapacity--Capacity of Binary symmetric and Binary Erasurechannels-Capacity of symmetrical and asymmetrical channels 10Computing channel capacity- Arimoto-Blahut algorithmFano’s inequality- Shannon’s Channel Coding TheoremModule 6: Continuous Sources and Channels: Informationmeasure for Continuous sources and channels-DifferentialEntropy- Joint, relative and conditional differential entropy10Mutual information- Gaussian channels- Mutual informationand Capacity calculation for Band limited Gaussian channelsShannon limit.Internal Assessment:40 MarksAssessment procedurei)Two internal tests, each having 15%ii)Tutorials/Assignments/ Mini projects having 10%iii)End Semester examination having 60%20Sem. ExamMarks;%151515152020
07EC6207 ADVANCED DIGITAL SIGNAL PROCESSINGCredits: 3-0-0: 3Year :2015Prerequisite: A basic course in Digital Signal ProcessingCourse Objectives To provide an overview of time frequency analysis which will help thestudents to design and implement various systemsTo familiarize the students with multirate signal processing principles.To equip the students to work with various linear prediction algorithms.To enable the students to appreciate various applications of nonlinear signalprocessing systems.To familiarize the students with power spectrum estimation of signals usingparametric and non-parametric methods.SyllabusReview of FIR and IIR Digital Filters, Park‐McClellanʹs method, Nonlinear and Nonstationarysignal Processing, Multirate system fundamentals, Time domain and frequency domainanalysis, Identities, Polyphase representation, Multirate filter banks, Forward and BackwardLinear Prediction, Optimum reflection coefficients for the Lattice Forward and BackwardPredictors, Solution of the Normal Equations, Levinson Durbin Algorithm, Schur Algorithm,Properties, Energy density spectrum, Estimation of the Autocorrelation and power spectrumof random signals, Non‐parametric spectral estimation, Parametric spectral estimation,Yule‐Walker , Burg method, AR , MA and ARMA models.Course Outcomes Design multirate systems for applications like Subband coding,Transmultiplexers, Digital audio systems, Adaptive filters etcDesign linear prediction systems using Levinson-Durbin algorithm.Have an understanding of Nonlinear and Nonstationary signal Processin
3. 07EC6229 Digital Image Processing 4. 07EC6239 Biomedical Signal Processing 5. 07EC6249 R F System Design Semester II Elective II 1. 07EC6228 Multirate Signal Processing 2. 07EC6238 Adaptive Signal Processing 3. 07EC6248 Advanced Optical Communication 4. 07EC6258 Antenna theory and Design 5. 07E
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KERALA AYURVEDA ACADEMY: THE DOCUMENTATION PROJECT 10 Kerala Ayurveda Academy & Wellness Center 691 S. Milpitas Blvd, Suite 206 Milpitas, CA 95035 888 275-9103 Name: _ Date: _ Welcome to Kerala Ayurveda Academy and Wellness Center.
