Indian Institute of Information Technology Bhagalpur

Computer Science and Engineering (CSE)

B.Tech. Course Curricula and Syllabus
Semester-V
Curricula:
Course
Course name L T P C
Code
EC301 Digital Signal Processing 3 0 0 3
CS301 Data Communication 3 0 0 3
CS302 Software Engineering 3 0 0 3
EC304 IoT and Embedded System 3 0 0 3
CS303 Artificial Intelligence 3 0 2 4
EC311 Digital Signal Processing LAB 0 0 3 2
EC312 IOT and Embedded System LAB 0 0 3 2
CS311 Software Engineering LAB 0 0 3 2
SAI-S-II Academia Internship 0 0 0 1

Syllabus:
Course Code Course name L T P C Year Semester
rd
EC301 Digital Signal Processing 3 0 0 3 3 5th
Course objective: The main objectives of the course are: to identify the signals and systems, apply the
principles of discrete-time signal analysis to perform various signal operations, apply the principles of z-
transforms to finite difference equations, apply the principles of Fourier transform analysis to describe the
frequency characteristics of discrete-time signals and systems, apply the principles of signal analysis to
filtering and use computer programming tools to process and visualize signals.
Topic Contents No. of Lectures
Review of discrete time signals, systems and transforms: Discrete time
signals, systems and their classification; Analysis of discrete time LTI
Module-I 08
systems: impulse response, difference equation, frequency response,
transfer function, DTFT, DTFS and Z-transform.
Ideal filter characteristics, low-pass, high-pass, band-pass and band-
stop filters, Paley-Wiener criterion, digital resonators, notch filters,
08
Module-II comb filters, Butterworth filter, chebyshev filter, inverse systems,
minimum phase, maximum phase and mixed phase systems.
Signal flow graph representation, basic structures for FIR and IIR
systems (direct, parallel, cascade and polyphase forms), transposition
theorem, ladder and lattice structures; Design of FIR filters using
Module-III 09
windows, frequency sampling, Remez algorithm and least mean square
error methods; Design of IIR filters using impulse invariance, bilinear
transformation and frequency transformations.
 Computational problem, DFT relations, DFT properties, fast Fourier
Module-IV transform (FFT) algorithms (radix-2, decimation-in-time, decimation- 08
in-frequency), Goertzel algorithm, linear convolution using DFT.
Finite word-length effects in digital filters: Fixed and floating point
representation of numbers, quantization noise in signal
representations, finite word-length effects in coefficient
Module-V 09
representation, round-off noise, SQNR computation and limit cycle;
Introduction to multi-rate signal processing: Decimation, interpolation,
poly-phase decomposition.
Total 42
1. S. K. Mitra, Digital Signal Processing: A Computer-Based Approach, Tata McGraw Hill, 2nd
edition, 2001.
Text 2. J. G. Proakis and D. G. Manolakis, Digital Signal Processing: Principles, Algorithms and
Applications, PHI, 4th edition, 2007.
Reference 1. A. V. Oppenheim and R. W. Shafer, Discrete-Time Signal Processing; PHI, 2nd edition, 2004.
Course Code Course Name L T P C Year Semester
CS301 Data Communications 3 0 0 3 3rd 5th
Course Objective: The objective of this course is to provide an overview of the concepts and fundamentals
of data communications networks. This subject introduces the basic of networks such as dataflow,
physical structures, network models, categories of networks which is necessary to study the computer
networking concepts in future semester. Introduce the student with the physical layer concepts in data
communication, transmission media, Analog and Digital transmission methodologies.
Topic Hour
Data communication basics: Data communication components, Data
Representation, Data Flow; Networks: Physical Structures, Network
Module I 6
Models, Categories of Networks, Interconnection Networks,
Internetwork: The Internet, Protocols and standards.
Data and signals: Analog signals, Digital signals; Transmission
impairment: Attenuation, distortion, noise; Data rate limits: Nyquist
Module II 6
rate, Shannon capacity; Performance: Bandwidth, throughput, latency,
bandwidth-delay product.
Digital transmission: line coding, PCM, ADPCM, DM; transmission
Module III 6
modes.
Analog transmission: modulation techniques; Bandwidth utilization,
Module IV multiplexing and spreading: FDM, WDM, TDM, STDM; xDSL; Spread 10
spectrum.
Transmission media: Guided (twisted pair, coaxial, fiber optic) and
unguided media; Balanced and unbalanced signalling; interfacing;
Module V Principles of switching; Local area networks: Ethernet, Fast Ethernet, 7
introduction to Gigabit Ethernet and WLANs; Hubs, bridges and
switches; Error detection and correction.
Total 35
1. Data Communications and Networking; B Forouzan; 5th Edition, Tata McGraw Hill;
2013.
Text
2. Data and Computer Communications; W Stallings; 10th Edition, Pearson India
Education Services Pvt.Ltd; 2013.
1. Computer Networks; A S Tanenbaum, ; 5th Edition, Pearson India Education Services
Reference
Pvt.Ltd; 2013.
Course Code Course Name L T P C Year Semester
rd
CS302 Software Engineering 3 0 0 3 3 5th
Course Objective: Concepts and techniques relevant to production of large software systems is discussed
in these course. It helps students to develop skills that will enable them to construct software of high
quality – software that is reliable, and that is reasonably easy to understand, modify and maintain.
Topic Hour
Introduction: Overview of System Engineering, Design and Analysis.
System Development Life Cycle, Waterfall Model, Spiral Model, Feasibility
Module I Analysis, Technical Feasibility, Cost- Benefit Analysis, COCOMO Model. 6
Software Process- Generic Process Model, Prescriptive Process Model,
Specialized, Unified Process, Etc.
Software Requirements and Software Design: Requirements Engineering,
System Requirement Specification – DFD, Data Dictionary, ER diagram,
Module II Process Organization & Interactions. System Design – Problem 7
Partitioning, Top-Down and Bottom-Up Design; Decision Tree, Decision
Table and Structured English; Functional Vs. Object- Oriented Approach.
Modeling with UML: Modeling Concepts and Diagrams - Use Case
Diagram- Class Diagrams - Interaction Diagrams - State Chart Diagrams –
Activity Diagrams - Package Diagrams - Component Diagrams –
Deployment Diagrams - Diagram Organization- Diagram Extensions.
Module III Design Process- Design Concepts: Abstraction, Architecture, Patterns, 7
Separation of Concerns, Modularity, Information Hiding, Functional
Independence, Refinement, Aspects, Refactoring, Object Oriented Design
Concepts, Design Classes- Design Model: Data, Architectural, Interface,
Component, Deployment Level Design Elements.
Software Implementation: Coding and Documentation - Structured
Programming, Object Oriented Programming, Information Hiding, Reuse,
System Structured Coding Techniques-Coding Styles-Standards and
Module IV 7
Guidelines. Documentation Guidelines-Modern Programming Language
Features: Type Checking-User Defined Data Types-Data Abstraction-
Exception Handling-Concurrency Mechanism.
Software Testing, Quality and Verification, Software Maintenance:
Software Quality- Software Quality Dilemma- Achieving Software Quality-
Testing: Strategic Approach to software Testing- Strategic Issues. Levels of
Testing, Integration Testing, Test case Specification, Reliability
Assessment. Strategies for Conventional Software, Object oriented
Module V 8
software, Validating Testing- System Testing- Art of Debugging, Validation
& Verification Metrics, Monitoring & Control. Software Maintenance-
Software Supportability, Reengineering-Business Process Reengineering,
Software Reengineering, Reverse Engineering- Restructuring, Forward
Engineering- Economics of Reengineering.
Total 35
1. Software Engineering – A Practitioner’s Approach; Roger S Pressman, ; 7th Edition, Mc-
Text
Graw Hill; 2017.
 2. Fundamentals of Software Engineering; Rajib Mall, ; 5th Edition, Prentice Hall India;
2018.

1.. Software Engineering Concepts; Richard Fairley, ; 2nd Edition, TMH; 2008.
2. Software Engineering; Ian Sommerville, ; 10th Edition, Pearson Education; 2017.
Reference 3.. An Integrated Approach to Software Engineering; P Jalote, ; 2nd Edition, Narosa
Publishing House; 2003.

Course Code Course name L T P C Year Semester

EC304 IoT & Embedded Systems 3 0 0 3 3rd 5th
Course objective: This main objective of this course facilitates to design, describe, validate and optimise
embedded electronic systems in different industrial application areas. More particularly, the architecture of
advanced processors, their instruction sets, interfacings to develop different kinds of systems.
1. To provide in depth knowledge about embedded processor, its hardware and software.
2. To explain programming concepts and embedded programming in C and assembly language
3. To explain real-time operating systems, inter-task communication and an embedded software
development tool.
Topic Contents No. of Lectures
An introduction to Embedded system design & modelling with
unified mark-up language; 8-bit and 16- bit, von Neumann and
Harvard architectures, CISC and RISC architectures; Advanced
RISC Machines, Open source core (LEOX), Introduction to
microcontrollers, ARM versions, ARM instruction set: assembly
Module-I 09
language, Thumb instruction set, memory organization, data
operations and flow control; Input/output mechanisms, isolated and
memory mapped IO; interrupts and real time operations, ARM
interrupts vectors, priorities and latency; co-processors; cache
memory and memory management.
Embedded Platforms: bus protocols, system bus configuration, USB
and SPI buses, DMA, ARM bus; memory devices: memory device
configuration, ROM, RAM, DRAM; I/O devices: timers, counters,
Module-II ADC & DAC, keyboards, displays and touch screens. Processes: 09
multiple tasks and multiple processes; process abstraction; context
switching: cooperative multitasking, pre-emptive multitasking,
process and object-oriented design
Operating Systems: operating systems and RTOS; scheduling polices;
inter-process communication; Networks: distributed embedded
Module-III 09
architectures: networks abstractions, hardware and software
architectures; networks for embedded systems: I2C bus, CAN bus.
An Introduction to Internet-of-Things, Sensing, Actuation, Basics of
Networking; Communication Protocols, Sensor Networks, Machine-
Module-IV to-Machine Communications, Wireless medium access issues, MAC 07
protocol survey, Survey routing protocols, Sensor deployment &
Node discovery, Data aggregation & dissemination
Developing IoTs: Introduction to Python, Introduction to different
Module-V 08
IoT tools, Developing applications through IoT tools, Developing
 sensor based application through embedded system platform,
Implementing IoT concepts with python; Domain specific
applications of IoT: Home automation, Industry applications,
Surveillance applications, Other IoT applications.
Total 42
1. A. N. Sloss, D. Symes, and C. Wright, ARM system developer's guide: Designing and
optimizing system software; Elsevier, 1st edition. 2008.
Text 2. Pethuru Raj and Anupama C. Raman, The Internet of Things: Enabling Technologies,
Platforms, and Use Cases,CRC Press, 2017.
1. Arshdeep Bahga and Vijay Madisetti, Internet of Things: A Hands-on Approach, Universities
Press, 2017.
Reference 2. W. Wolf, Computers as components: Principles of embedded computing system design;
Elsevier, 3rd edition, 2013.

Course Code Course name L T P C Year Semester

rd
CS303 Artificial Intelligence 3 0 2 4 3 5th
Course Objective: The objective of the course is to present an overview of artificial intelligence (AI)
principles and approaches. Develop a basic understanding of the building blocks of AI as presented
in terms of intelligent agents: Search, Knowledge representation, inference, logic, and learning.

Topic Contents No. of Lectures

Module 1 Fundamental issues in intelligent systems: History of artificial 2
intelligence; philosophical questions; fundamental
definitions; philosophical questions; modeling the world; the
role of heuristics.
Module 2 Search and constraint satisfaction: Problem spaces; brute- 10
force search; best-first search; two-player games; constraint
satisfaction.
Module 3 Knowledge representation and reasoning: Review of 8
propositional and predicate logic; resolution and theorem
proving; non-monotonic inference; probabilistic reasoning;
Bayes theorem.
Module 4 AI planning systems: Definition and examples of planning 8
systems; planning as search; operator-based planning;
propositional planning.
Module 5 Sequential decision making: Achieving behaviour by 7
specifying rewards, Markov Decision Problems.
Total 35

Text Books 1. Stuart Russell and Peter Norvig: Artifical Intelligence: A Modern
Approach, Pearson; Third edition (2013).
2. Elaine Rich, Kevin Knight and Shivashankar B Nair, Artificial Intelligence,
Tata McGraw Hill, 3rd Edition 2009.
Reference
 1. N. J. Nilsson, "Principles of Artificial Intelligence", Narosa Publishing House,
Books
1980.
 2. Clocksin & Mellish, Programming in PROLOG, Narosa Publ. House.