Artificial Intelligence in Communication

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ARTIFICIAL INTELLIGENCE IN 4716006
FREE PDF 4716006
Code: 4716006 Credits: 4 Semester 1 EACE

Artificial Intelligence in Communication

Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.

Artificial Intelligence in Communication Syllabus — Unit-wise Content

The official GTU curriculum for Artificial Intelligence in Communication (subject code 4716006) as prescribed for EACE · Semester 1 divides the course into 5 units, covering 39 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (4716006)

Unit 1 UNIT-I

8 lecture hours

  • Introduction to AI and Communication System Basic about AI, The AI Problems
  • The Underlying Assumption
  • AI Techniques
  • The Level Of The Model
  • Criteria For Success
  • Some General References
  • One Final Word
  • Various aspects of communication systems
  • wireless system design
  • where machine learning can be applied in various OSI layers of a communication system
  • how real-time schedulers can benefit from advanced machine learning techniques

Unit 2 UNIT-II

10 lecture hours

  • Type of Learning and Applications Supervised Learning and its applications in wireless communication systems
  • Applications in modulation classification
  • adaptive modulation and coding mechanisms for wireless systems, etc
  • Unsupervised Learning and its applications in wireless systems
  • Use of principal component analysis in massive Wef-AY-2021-22 mimo system design
  • auto encoders in wireless communication transceiver design, etc

Unit 3 UNIT-III

8 lecture hours

  • State Space Search & Heuristic Search Techniques Defining The Problems As A State Space Search
  • Production Systems
  • Production Characteristics
  • Production System Characteristics, And Issues In The Design of Search Programs
  • Additional Problems
  • Generate- And-Test
  • Hill Climbing
  • Best-First Search
  • Problem Reduction
  • Constraint Satisfaction
  • Means-Ends Analysis

Unit 4 UNIT-IV

6 lecture hours

  • Predicate Logic Representation Simple Facts In Logic
  • Representing Instance And Isa Relationships
  • Computable Functions and Predicates

Unit 5 UNIT-V

10 lecture hours

  • Introduction To Prolog Syntax and Numeric Function
  • Basic List Manipulation Functions In Prolog
  • Predicates and Conditional
  • Output and Local Variables
  • Iteration and Recursion
  • Property Lists and Arrays
  • Miscellaneous Topics
  • LISP and Other AI Programming Languages

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