# Computer Engineering Semester 7

Computer Engineering Semester 7

 Digital Signal Processing Discrete Time Signal 1.1 Introduction to Digital Signal Processing, Discrete Time Signals, Sampling and Reconstruction, Standard DT Signals, Concept of Digital Frequency, Representation of DT signal using Standard DT Signals, Signal Manipulations(shifting, addition, subtraction, multiplication), Classification of Signals, Linear Convolution formulation(without mathematical proof), Circular Convolution formulation(without mathematical proof), Matrix Representation of Circular Convolution, Linear by Circular Convolution. Auto and Cross Correlation formula evaluation, 02 Discrete Time System 2.1 Introduction to Discrete Time System, Classification of DT Systems (Linear/Non Linear, Causal/Non Causal, Time Invariant/Time Variant Systems, Stable/ Unstable), BIBO Time Domain Stability Criteria. LTI system, Concept of Impulse Response and Step Response. 2.2 Concept of IIR System and FIR System, Output of IIR and FIR DT system using Time Domain Linear Convolution formula Method. 03 Discrete Fourier Transform 3.1 Introduction to DTFT, DFT, Relation between DFT and DTFT, Properties of DFT without mathematical proof (Scaling and Linearity, Periodicity, Time Shift and Frequency Shift, Time Reversal, Convolution Property and Parsevals’ Energy Theorem). DFT computation using DFT properties. 3.2 Transfer function of DT System in frequency domain using DFT. Linear and Circular Convolution using DFT. Response of FIR system calculation in frequency domain using DFT. 04 Fast Fourier Transform 4.1 Radix-2 DIT-FFT algorithm, DIT-FFT Flowgraph for N=4, 6 & 8, InveFFT algorithm. Spectral Analysis using FFT, Comparison of complex and real, multiplication and additions of DFT and FFT. 05 DSP Algorithms 5.1 Carls’ Correlation Coefficient Algorithm, Fast Circular Convolution Algorithm, Fast Linear Convolution Algorithm, Linear FIR filtering using Fast Overlap Add Algorithm and Fast Overlap Save Algorithm, 06 DSP Processors and Application of DSP 6.1 Need for Special architecture of DSP processor, Difference between DSP processor & microprocessor, A general DSP processor TMS320C54XX series, Case study of Real Time DSP applications to Speech Signal Processing and Biomedical Signal Processing. Term Work: · Term work shall consist of minimum 08 assignments and course project. · Journal must include at least 1 assignment on each module and two quiz. · The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. Text Books : 1. Ashok Ambardar, ‘Digital Signal Processing’, Cengage Learning, 2007, ISBN : 978-81-315-0179-5. 2. Emmanuel C. Ifeachor, Barrie W. Jervis, “Digital Signal Processing: A Practical Approach”, Pearson Education ISBN 0-201-59619- 9 3. S. Salivahanan, A. Vallavaraj, C. Gnanapriya, ‘Digital Signal Processing’ TataMcgraw Hill Publication First edition (2010). ISBN 978-0-07-066924-6. 4. Avtar Signh, S.Srinivasan,”Digital Signal Processing’, Thomson Brooks/Cole, ISBN : 981-243-254-4 Cryptography and System Security Introduction 1.1 Security Attacks, Security Goals, Computer criminals, Methods of defense, Security Services, Security Mechanisms 02 Basics of Cryptography 2.1 Symmetric Cipher Model, Substitution Techniques, Transportation Techniques, Other Cipher Properties- Confusion, Diffusion, Block and Stream Ciphers. 03 Secret Key Cryptography 3.1 Data Encryption Standard(DES), Strength of DES, Block Cipher Design Principles and Modes of Operations, Triple DES, International Data Encryption algorithm, Blowfish, CAST-128. 04 Public Key Cryptography 4.1 Principles of Public Key Cryptosystems, RSA Algorithm, Diffie- Hellman Key Exchange 05 Cryptographic Hash Functions 5.1 Applications of Cryptographic Hash Functions, Secure Hash Algorithm, Message Authentication Codes – Message Authentication Requirements and Functions, HMAC, Digital signatures, Digital Signature Schemes, Authentication Protocols, Digital Signature Standards. 06 Authentication Applications 6.1 Kerberos, Key Management and Distribution, X.509 Directory Authentication service, Public Key Infrastructure, Electronic Mail Security: Pretty Good Privacy, S/MIME.7.1 Program Security Secure programs, Nonmalicious Program Errors, Malicious Software – Types, Viruses, Virus Countermeasures, Worms, Targeted Malicious Code, Controls against Program Threats. 7.2 Operating System Security Memory and Address protection, File Protection Mechanism, User Authentication. 7.3 Database Security Security Requirement, Reliability and Integrity, Sensitive data, Inference, Multilevel Databases 7.4 IDS and Firewalls Intruders, Intrusion Detection, Password Management, Firewalls- Characteristics, Types of Firewalls, Placement of Firewalls, Firewall Configuration, Trusted systems. 08 8.1 IP Security Overview, Architecture, Authentication Header, Encapsulating Security Payload, Combining security Associations, Internet Key Exchange, Web Security: Web Security Considerations, Secure Sockets Layer and Transport Layer Security, Electronic Payment. 8.2 Non-cryptographic protocol Vulnerabilities DoS, DDoS, Session Hijacking and Spoofing, Software Vulnerabilities- Phishing, Buffer Overflow, Format String Attacks, SQL Injection. Term Work: Term work should consist of at least 10experiments, 2 assignments based on above theory syllabus. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. Theory Examination: 1. Question paper will comprise of total 6 questions, each of 20 Marks. 2. Only 4 questions need to be solved. 3. Question 1 will be compulsory and based on maximum part of the syllabus. 4. Remaining questions will be mixed in nature (for example suppose Q.2 has part (a) from module 3 then part (b) will be from any module other than module 3) In question paper, weightage of each module will be proportional to number of respective lecture hours as mentioned in the syllabus. Text Books: 1. Cryptography and Network Security: Principles and Practice 5th edition, William Stallings, Pearson. 2. Network Security and Cryptography 2nd edition, Bernard Menezes, Cengage Learning. 3. Cryptography and Network, 2nd edition, Behrouz A Fourouzan, Debdeep Mukhopadhyay, TMH.

 Artificial Intelligence Introduction to Artificial Intelligence 1.1 Introduction , History of Artificial Intelligence, Intelligent Systems: Categorization of Intelligent System, Components of AI Program, Foundations of AI, Sub-areas of AI, Applications of AI, Current trends in AI. 02 Intelligent Agents 2.1 Agents and Environments, The concept of rationality, The nature of environment, The structure of Agents, Types of Agents, Learning Agent. 03 Problem solving 3.1 Solving problem by Searching : Problem Solving Agent, Formulating Problems, Example Problems. 3.2 Uninformed Search Methods: Breadth First Search (BFS), Depth First Search (DFS) , Depth Limited Search, Depth First Iterative Deepening(DFID), Informed Search Methods: Greedy best first Search ,A* Search , Memory bounded heuristic Search. 3.3 Local Search Algorithms and Optimization Problems: Hillclimbing search Simulated annealing, Local beam search,Genetic algorithms. 3.4 Adversarial Search: Games, Optimal strategies, The minimax algorithm , Alpha-Beta Pruning. 04 Knowledge and Reasoning 4.1 Knowledge based Agents, The Wumpus World, The Propositional logic, First Order Logic: Syntax and Semantic, Inference in FOL, Forward chaining, backward Chaining. 4.2 Knowledge Engineering in First-Order Logic, Unification, Resolution, Introduction to logic programming (PROLOG). 4.3 Uncertain Knowledge and Reasoning: Uncertainty, Representing knowledge in an uncertain domain, The semantics of belief network, Inference in belief network. 05 Planning and Learning 5.1The planning problem, Planning with state space search, Partial order planning, Hierarchical planning, Conditional Planning. 5.2 Learning: Forms of Learning, Inductive Learning, Learning Decision Tree. 5.3 Expert System: Introduction, Phases in building Expert Systems, ES Architecture, ES vs Traditional System. 06 Applications 6.1 Natural Language Processing(NLP), Expert Systems. Term Work: The distribution of marks for term work shall be as follows: · Laboratory work (experiments/case studies): ………….. (15) Marks. · Assignment:………..………………………………… (05) Marks. · Attendance ………………………………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. Text Books: 1. Stuart J. Russell and Peter Norvig, “Artificial Intelligence A Modern Approach “Second Edition” Pearson Education. 2. Saroj Kaushik “Artificial Intelligence” , Cengage Learning. 3. George F Luger “Artificial Intelligence” Low Price Edition , Pearson Education., Fourth edition. Advanced Algorithms Introduction 1.1 Asymptotic notations Big O, Big Q,Big W,o ,w notations ,Proofs of master theorem, applying theorem to solve problems 02 Advanced Data Structures 2.1 Red-Black Trees: properties of red-black trees , Insertions , Deletions 2.2 B-Trees and its operations 2.3 Binomial Heaps: Binomial trees and binomial heaps, Operation on Binomial heaps 03 Dynamic Programing 3.1 matrix chain multiplication, cutting rod problem and its analysis 04 Graph algorithms 4.1 Bellman ford algorithm, Dijkstra algorithm, Johnson’s All pair shortest path algorithm for sparse graphs 05 Maximum Flow 5.1 Flow networks , the ford Fulkerson method ,max bipartite matching , push Relabel Algorithm , The relabel to front algorithm 06 Linear Programing 6.1 Standard and slack forms, Formulating problems as linear programs, simplex algorithm, Duality, Initial basic feasible solution 07 Computational Ggeometry 7.1 Line Segment properties, Determining whether any pair of segment intersects, finding the convex hull, Finding the closest pair of points. Term Work: Term work should consist of at least 6 experiments, 2 assignments based on above theory syllabus. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks Text Books: 1. T.H. Coreman , C.E. Leiserson, R.L. Rivest, and C. Stein, “Introduction to algorithms”,2nd edition , PHI publication 2005 2. Ellis Horowitz , Sartaj Sahni , S. Rajsekaran. “Fundamentals of computer algorithms” University press

 Image Processing Digital Image and Video Fundamentals 1.1 Introduction to Digital Image, Digital Image Processing System, Sampling and Quantization, Representation of Digital Image, Connectivity, Image File Formats : BMP, TIFF and JPEG. Colour Models (RGB, HSI, YUV) Introduction to Digital Video, Chroma Sub-sampling, CCIR standards for Digital Video 02 Image Enhancement 2.1 Gray Level Transformations, Zero Memory Point Operations, Histogram Processing, Neighbourhood Processing, Spatial Filtering, Smoothing and Sharpening Filters. Homomorphic Filtering 03 Image Segmentation and Representation 3.1 Detection of Discontinuities, Edge Linking using Hough Transform, Thresholding, Region based Segmentation, Split and Merge Technique, Image Representation and Description, Chain Code, Polygonal Representation, Shape Number, Moments. 04 Image Transform 4.1 Introduction to Unitary Transform, Discrete Fourier Transform(DFT), Properties of DFT, Fast Fourier Transform(FFT), Discrete Hadamard Transform(DHT), Fast Hadamard Transform(FHT), Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT), 05 Image Compression 5.1 Introduction, Redundancy, Fidelity Criteria, 5.2 Lossless Compression Techniques : Run Length Coding, Arithmetic Coding, Huffman Coding, Differential PCM,5.3 Lossy Compression Techniques: Improved Gray Scale Quantization, Vector Quantization, JPEG, MPEG-1. 06 Binary Image Processing 6.1 Binary Morphological Operators, Hit-or-Miss Transformation, Boundary Extraction, Region Filling, Thinning and Thickening, Connected Component Labeling, Iterative Algorithm and Classical Algorithm Term Work: Term work should consist of at least 08 experiments. Journal must include at least 1 assignment on each module and two quiz. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. Text Books : 1. Rafel C. Gonzalez and Richard E. Woods, ‘Digital Image Processing’, Pearson Education Asia, Third Edition, 2009, 2. S. Jayaraman, E.Esakkirajan and T.Veerkumar, “Digital Image Processing” TataMcGraw Hill Education Private Ltd, 2009, 3. Anil K. Jain, “Fundamentals and Digital Image Processing”, Prentice Hall of India Private Ltd, Third Edition 4. S. Sridhar, “Digital Image Processing”, Oxford University Press, Second Edition, 2012. 5. Robert Haralick and Linda Shapiro, “Computer and Robot Vision”, Vol I, II, Addison Wesley, 1993. Software Architecture Basic Concepts 1.1 Concepts of Software Architecture 1.2 Models. 1.3 Processes. 1.4 Stakeholders 03 02 Designing Architectures 2.1 The Design Process. 2.2 Architectural Conception. 2.3 Refined Experience in Action: Styles and Architectural Patterns. 2.4 Architectural Conception in Absence of Experience. 03 Connectors 3.1 Connectors in Action: A Motivating Example. 3.2 Connector Foundations. 3.3 Connector Roles. 3.4 Connector Types and Their Variation Dimensions. 3.5 Example Connectors. 04 Modeling 4.1 Modeling Concepts. 4.2 Ambiguity, Accuracy, and Precision. 4.3 Complex Modeling: Mixed Content and Multiple Views. 4.4 Evaluating Modeling Techniques. 4.5 Specific Modeling Techniques. 05 Analysis 5.1 Analysis Goals. 5.2 Scope of Analysis. 5.3 Architectural Concern being Analyzed. 5.4 Level of Formality of Architectural Models.5.5 Type of Analysis. 5.6 Analysis Techniques. 06 Implementation and Deployment 6.1 Concepts. 6.2 Existing Frameworks. 6.3 Software Architecture and Deployment. 6.4 Software Architecture and Mobility. 07 Conventional Architectural styles 7.1 Pipes and Filters 7.2 Event- based, Implicit Invocation 7.3 Layered systems 7.4 Repositories 7.5 Interpreters 7.6 Process control 08 Applied Architectures and Styles 8.1 Distributed and Networked Architectures. 8.2 Architectures for Network-Based Applications. 8.3 Decentralized Architectures. 8.4 Service-Oriented Architectures and Web Services. 09 Designing for Non-Functional Properties 9.1 Efficiency. 9.2 Complexity. 9.3 Scalability and Heterogeneity. 9.4 Adaptability. 9.5 Dependability. 10 Domain-Specific Software Engineering 10.1 Domain-Specific Software Engineering in a Nutshell. 10.2 Domain-Specific Software Architecture. 10.3 DSSAs, Product Lines, and Architectural Styles. Term Work: The distribution of marks for term work shall be as follows: · Laboratory work (experiments):…………………….. (20) Marks. · Attendence:…….……………………………………… (05) Marks. TOTAL: ……………………………………………………. (25) Marks. Text Books: 1. “Software Architecture: Foundations, Theory, and Practice” by Richard N. Taylor, Nenad Medvidovic, Eric Dashofy, ISBN: 978-0-470-16774-8 2. M. Shaw: Software Architecture Perspectives on an Emerging Discipline, Prentice-Hall. 3. Len Bass, Paul Clements, Rick Kazman: Software Architecture in Practice, Pearson.