Duration 3 Years |
Level Doctorate |
Type Degree |
Eligibility Post Graduation |
Ph.D. Electrical and Electronics Engineering or Doctor of Philosophy in Electrical and Electronics Engineering is Doctorate Electrical Engineering course. It is subjective in nature and undertakes the research work in depth. After completing the doctorate degree scholars need to submit their ‘thesis’ and then they deserve the respective degree. Regarding Electrical and Electronics Engineering, it is a field of engineering that generally deals with the study and application of electricity, electronics and electromagnetism. The duration of the program is minimum two years from the date of registration (three years for external candidates) and maximum five to six years. The minimum qualifications and other eligibility criteria for admission are the same as for regular full-time students. Ph.D. is a broad-based course involving a minimum course credit requirement and research thesis.
Syllabus of Electrical and Electronics Engineering as prescribed by various Universities and Colleges.
Sr. No. |
Subjects of Study |
1 |
Research Methodology |
2 |
Scientific Communication |
3 |
Specialization paper (Recent trends in Electronics and Communication Engineering) |
Detailed Syllabus View:
Paper I (Research Methodology) |
|
Sect. |
Subjects of Study |
A |
Common to all faculties |
|
1) Introduction to Research Methodology: Meaning of Research, Objectives of Research, Motivations in Research, Types of Research, Research Approaches, Significance of Research, Research Methods v/s Methodology, Research and Scientific Methods, Research Process, Criteria of Good Research. |
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2) Defining the Research Problem: What is Research Problem? Selecting the Problem, Necessity of and Techniques in defining the problem. |
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3) Research Design: Meaning, Need, Features of Good Design, Concepts, Types. Basic Principles of Experimental Design, Developing a Research Plan. |
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4) Sample Design: Implication, Steps. Criteria for selecting a sample procedure, Characteristics of Good Sampling Procedure, Types of Sample Design, Selecting Random Samples, Complex random sampling Design. |
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5) Measurement and Scaling Techniques: Measurement in Research, Measurement Scales, Sources of Errors in measurement, Tests of the Second measurement, Technique of developing Measurement Tools, Meaning of Scaling, Scale Classification Bases, Important Scaling Techniques, Scale Construction Techniques. |
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6) Methods of Data Collection: Collection of Primary Data, Observation Method, Interview method, Collection of Data through questionnaire and Schedules, Other methods. Collection of Secondary Data, Selection of an appropriate method for data collection, Case Study Method, Guidelines for developing a questionnaire, successful interviewing. Survey v/s experiment. |
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7) Processing and analysis of Data: Processing Operations (Meaning, Problems), Data Analysis (Elements), Statistics in Research, Measures of Central Tendency, Dispersion, Asymmetry, and Relationship. Regression Analysis, Multiple correlation and Regression, Partial Correlation, Association in case of Attributes. |
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8) Sampling Fundamentals: Definition, Need, Important sampling Distribution, Central limit theorem Sampling Theory, Sandler’s Atest, Concept of Standard Error, Estimation, estimating the population means, proportion. Sample size and its determination, Determination of sample size Based on, i) Precision Rate and Confidence level ii) Bayesian Statistics. |
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9) Testing of Hypothesis: Meaning, Basic concepts, Flow diagram, Power of a hypothesis test, Important parametric tests, Hypothesis Testing of Means, Differences between Means, Comparing Two related samples, Testing of Proportion, Difference between proportions, comparing variance to hypothesized population variance, Equality of variances of two normal populations, hypothesis testing of Correlation coefficients, Limitations of Tests of hypothesis. |
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10) Chi-square test: Applications, Steps, characteristics, limitations |
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11) Analysis of Variance and Covariance: Basic Principles, techniques, applications, Assumptions, limitations. |
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12) Analysis of Non-parametric or distribution-free Tests: Sign Test, Fisher-Irwin Test, McNemer Test, Wilcoxon Matched Pair Test (Signed Rank Test), Rank. |
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13) Sum Tests: a) Wilcoxon-Mann-Whitney Test b) Kruskal-Wallis Test, one sample Runs Test, Spearman’s Rank Correlation, Kendall’s Coefficient of Concordance, Multivariate Analysis Techniques: Characteristics, Application, Classification, Variables, Techniques, Factor Analysis (Methods, Rotation), Path Analysis. |
B |
Faculty of Electronics & Communication |
Research Areas: |
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Exercise: |
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Paper II (Scientific Communication) |
|
Sect. |
Subjects of Study |
A |
Common for all faculties |
|
1. Basics of Communication skill |
B |
Faculty of Electronics & Communication |
Exposure to- |
|
Paper III (Faculty of Electronics & Communication Engg.) |
|
A |
Recent Trends in Electronics & Communication |
|
1. Data and Communication Networks |
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• Introduction to computer communication networks and layered architecture overview. Packet switching. |
2. Wavelets and its applications |
|
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• Introduction to time-frequency analysis; the how and what and why about wavelets. |
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3. VLSI design and technology |
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• Basics of VLSI Design, Review of MOS transistor models. CMOS logic families including static, dynamic and dual-rail logic. Integrated Circuit Layout: Design Rules, Parasitics. Building blocks: ALU's, FIFO's, counters. VLSI system design: data and control path design, floor planning, Design methodology: Introduction to hardware description languages (VHDL), logic, circuit and layout verification. Design examples. |
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Digital Speech and Image Processing: |
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• Discrete-time signal and system, Classification of signals, The concept of frequency in continuous time and discrete-time signals |
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Exts/ References |
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1. Digital Image Processing by Rafael C. Gonzalez, Richard E. Woods, Prentice Hall Publication |
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