This note covers the following
topics: Basic codes and constructions, Algebraic Geometry Codes, Limits on
Performance of Codes, Algebraic decoding, Algebraic decoding, Linear time
decoding, Decoding from random errors and erasures, Applications in complexity
theory and Complexity results in coding theory.
This note covers the following topics:
The naive way of coding, Coding schemes for binary channels and Shannon theorem,
Shannon theorem, Exponential growth rate, Binary codes, The Hamming bound and
perfect codes, The Gilbert-Varshamov bound, Error probability estimations, Union
bound for BER, State representations and trellises of general codes,
Convolutional codes, Tanner graphs and factor graphs.
This note covers the following topics: Inductive Definitions, Transition
Systems, Defining a Language, Concrete Syntax, Abstract Syntax Trees, Abstract
Binding Trees, Functional Language, Control and Data Flow, Imperative Functional
Programming, Cost Semantics and Parallelism, Data Structures and Abstraction,
Lazy Evaluation, Dynamic Typing, Subtyping and Inheritance, Concurrency.
This book explains the following topics: Linear Codes, Probability
as Fancy Counting and the q-ary Entropy Function, Combinatorics, The Greatest
Code of Them All: Reed-Solomon Codes, What Happens When the Noise is Stochastic:
Shannon's Theorem, Bridging the Gap Between Shannon and Hamming: List Decoding,
Code Constructions, Code Concatenation, Algorithms, Decoding Concatenated Codes,
Efficiently Achieving the Capacity of the BSCp, Efficient Decoding of
Reed-Solomon Codes, Efficiently Achieving List Decoding Capacity, Applications.
Author(s): Venkatesan Guruswami, Atri Rudra and Madhu
This note introduces the theory of
error-correcting codes to computer scientists. This theory, dating back to the
works of Shannon and Hamming from the late 40's, overflows with theorems,
techniques, and notions of interest to theoretical computer scientists. The
course will focus on results of asymptotic or algorithmic significance.
Principal topics include: Construction and existence results for
error-correcting codes, Limitations on the combinatorial performance of
error-correcting codes, Decoding algorithms, Applications in computer science.
This note covers the following topics: Basic Theories, Basic Data
Structures, Function Theory, Program Theory, Programming Language, Recursive
Definition, Theory Design and Implementation, Concurrency and Interaction.
This book covers the following topics: Computer Architecture,
Functions, Files, Reading and Writing Simple Records, Developing Robust
Programs, Sharing Functions with Code Libraries, Intermediate Memory Topics,
High-Level Languages and Optimization.
emphasizes the role of computer languages as vehicles for expressing knowledge
and it presents basic principles of abstraction and modularity, together with
essential techniques for designing and implementing computer languages.