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Sniper bullet homes in on target like a guided missile

DARPA developed a specialised .50-caliber round combined with optical sighting technology that allows for real-time...

New Products

Silicon Labs roll out wireless, power-saving SoC family (24/02/16)
Fuel-cell maker to develop week-long battery life for smartphones (09/02/16)
16nm heterogeneous multi-processing SoCs target ADAS apps (13/01/16)
Microchip unveils ecosystem programme for embedded designers (16/12/15)
Software platform to optimise CE device connectivity in cars (30/10/15)
IoT gateway touts embedded analytics (26/10/15)
SoM enables embedded designs with low-power consumption (02/09/15)
RTOS from Mentor targets connected embedded devices (08/05/15)
Telit's ARM Compiler takes embedded processing to top speed (06/04/15)
Low-cost development platforms target image sensing, audio (16/03/15)
Synopsys, Freescale help speed up automotive projects (06/03/15)
Analytics platform supports large IoT data analysis (04/03/15)
Dev kit enables fast multi-camera calibration in vehicles (25/02/15)
ARM starter kit brings smart devices to the cloud (25/02/15)
Cloud service protects Android apps from malware, hackers (25/02/15)

More Embedded New Products

News & Trends

Robots: Spotlight on the hidden face of automation (18/05/16)
Embedded Vision Summit highlights car safety rules (10/05/16)
Scrutinising the new phase of ransomware (25/04/16)
Wind River avionics system enables Airbus Helicopters (22/04/16)
Checklist to get embedded software quality right from start (28/03/16)
AlphaGo defeats S. Korean grandmaster in Go tournament (16/03/16)
Toyota develops wearable device for the blind (14/03/16)
Embedded design survey reveal safety concerns (11/03/16)
Embedded World turns spotlight to security (29/02/16)
Fujitsu cracks multi-source data encryption conundrum (16/02/16)
NASA cites Astrobotic Technology as key to Mars exploration (08/02/16)
UK to increase IT workers' salary in a bid to cut migration (01/02/16)
Connected cars: Drawing the line in securing personal data (01/02/16)
India to design first 64bit RISC-V processor (28/01/16)
Embedded board standards take on spacecraft design (25/01/16)

More Embedded News & Trends

Technical Archives

Exploring Embedded DisplayPort (18/05/16)
Prototype to production: A hands-on guide (16/05/16)
Programming: Managing the risk of pointers (10/05/16)
Techniques for debugging Cortex-M MCU (09/05/16)
Accelerate development of IoT devices (26/04/16)
Behind the scenes: MCU start-up code (14/04/16)
Compress 8051 code with improved data choices (13/04/16)
Developing embedded software using Agile methodology (11/04/16)
Using Python to automate measurements (07/04/16)
Understanding embedded hypervisors (05/04/16)
How to create abstract data type in C (28/03/16)
Developing application in SDSoC (Part 3) (23/03/16)
Evaluating heat in vehicles' instrument panels (17/03/16)
Do you really know your debugger? (08/03/16)
Self-testing methods: Software failure (07/03/16)

More Embedded Technical Archives

Application Notes

Examine advanced electronics for stealth, comms in F-35 (23/11/15)
A look at timers (14/10/15)
Indian's wearable system bags 2nd place in global challenge (12/08/15)
Utilising TMS320C6748/C6746/C6742 bootloader (04/09/14)
Guide to DRV2605 driver setup (07/08/14)
Guide to DS28C22DEMOK authentication demo stick (24/07/14)
Software start up, optimisation for automotive MCU (03/07/14)
Dealing with crystal failure for MPC57XX (28/05/14)
Programming MMPF0200 OTP (27/05/14)
U-Boot debugging with CodeWarrior (26/05/14)
Practical approach to hardware semaphores (25/04/14)
How to design a project using IAR Eclipse Plugin (10/01/14)
Intro to DSC56800EX Quick Start Devt Environment (08/01/14)
Port U-Boot, Linux to T4240 systems (06/01/14)
Employ DSPI as slave on MQX 3.8 (02/01/14)

More Embedded Application Notes

eeUniversity

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Lecture 28
Current Mode ICs

Lecture 1
Introduction to Artificial Intelligence

Lecture 2
Intelligent Agents

Lecture 3
State Space Search

Lecture 4
Uninformed Search

Lecture 5
Informed Search

Lecture 6
Informed Search - 2

Lecture 7
Two Players Games - I

Lecture 8
Two Players Games - II

Lecture 9
Constraint Satisfaction Problems - 1

Lecture 10
Constraint Satisfaction Problems 2

Lecture 11
Knowledge Representation and Logic

Lecture 12
Interface in Propositional Logic

Lecture 13
First Order Logic

Lecture 14
Reasoning Using First Order Logic

Lecture 15
Resolution in FOPL

Lecture 18
Semantic Net

Lecture 19
Reasoning in Semantic Net

Lecture 20
Frames

Lecture 21
Planning - 1

Lecture 22
Planning - 2

Lecture 33
Introduction to Learning - II

Lecture 34
Rule Induction and Decision Trees - I

Lecture 35
Rule Induction and Decision Trees - II

Lecture 36
Leavning Using neural Networks - I

Lecture 37
Learning Using Neural Networks - II

Lecture 38
Probabilistic Learning

Lecture 39
Natural Language Processing - I

Lecture 40
Natural Language Processing II

Lecture 1
Introduction to Artificial Intelligence

Lecture 2
Problem Solving by Search

Lecture 3
Searching with Costs

Lecture 4
Informed State Space Search

Lecture 5
Heuristic Search: A* and Beyond

Lecture 6
Problem Reduction Search: AND/OR Graphs

Lecture 7
Searching Game Trees

Lecture 8
Knowledge Based Systems: Logic and Deduction

Lecture 9
First Order Logic

Lecture 10
Inference in First Order Logic

Lecture 11
Resolution - Refutation Proofs

Lecture 12
Resolution Refutation Proofs

Lecture 13
Logic Programming : Prolog

Lecture 14
Prolog Programming

Lecture 15
Prolog: Exercising Control

Lecture 16
Additional Topics

Lecture 17
Introduction to Planning

Lecture 18
Partial Order Planning

Lecture 19
GraphPLAN and SATPlan

Lecture 20
SATPlan

Lecture 21
Reasoning Under Uncertainity

Lecture 22
Bayesian Networks

Lecture 23
Reasoning with Bayes Networks

Lecture 24
Reasoning with Bayes Networks (Contd.)

Lecture 25
Reasoning Under Uncertainity: Issues

Lecture 26
Learning : Decision Trees

Lecture 27
Learning : Neural Networks

Lecture 28
Back Propagation Learning

Lecture 8
Analysis Using Matlab

Lecture 9
Sinusoidal steady state

Lecture 10
Transfer Function and Pole-Zero Domain 1

Lecture 11
Transfer Function and Pole-Zero Domain 2

Lecture 12
The Sinusoid

Lecture 16
Power ports

Lecture 23
DC Machines Part 1

Lecture 24
DC Machines Part 2

Lecture 25
DC Generators Part 1

Lecture 26
DC Generators Part 2

Lecture 27
DC Motors Part 1

Lecture 28
DC Motors Part 2

Lecture 29
DC Motor Part 3

Lecture 1
Control Engineering

Lecture 2
Control Engineering

Lecture 3
Control Engineering

Lecture 4
Control Engineering

Lecture 5
Control Engineering

Lecture 6
Control Engineering

Lecture 7
Control Engineering

Lecture 8
Control Engineering

Lecture 9
Control Engineering

Lecture 10
Control Engineering

Lecture 11
Control Engineering

Lecture 12
Control Engineering

Lecture 13
Control Engineering

Lecture 14
Control Engineering

Lecture 15
Control Engineering

Lecture 16
Control Engineering

Lecture 17
Control Engineering

Lecture 18
Control Engineering

Lecture 19
Control Engineering

Lecture 20
Control Engineering

Lecture 21
Control Engineering

Lecture 22
Control Engineering

Lecture 23
Control Engineering

Lecture 24
Control Engineering

Lecture 25
Control Engineering

Lecture 26
Control Engineering

Lecture 27
Control Engineering

Lecture 28
Control Engineering

Lecture 29
Control Engineering

Lecture 30
Control Engineering

Lecture 31
Control Engineering

Lecture 32
Control Engineering

Lecture 33
Control Engineering

Lecture 34
Control Engineering

Lecture 35
Control Engineering

Lecture 36
Control Engineering

Lecture 37
Control Engineering

Lecture 38
Control Engineering

Lecture 47
Control Engineering

Lecture 1
Digital Signal Processing Introduction

Lecture 2
Digital Signal Processing Introduction (Cont.)

Lecture 3
Digital Systems

Lecture 4
Characterization, Description and Testing of Digital Systems

Lecture 5
LTI Systems Step and Impulse Responses, Convolution

Lecture 6
Inverse Systems, Stability, FIR and IIR

Lecture 7
FIR & IIR; Recursive & Non Recursive

Lecture 8
Discrete Time Fourier Transform

Lecture 9
Discrete Fourier Transform (DFT)

Lecture 1
Introduction to Embedded Systems

Lecture 2
Embedded Hardware

Lecture 3
PIC: Instruction Set

Lecture 4
PIC Peripherals On Chip

Lecture 5
ARM Processor

Lecture 6
More ARM Instructions

Lecture 7
ARM: Interrupt Processing

Lecture 8
Digital Signal Processors

Lecture 9
More on DSP Processors

Lecture 10
System On Chip (SOC)

Lecture 11
Memory

Lecture 12
Memory Organization

Lecture 13
Virtual Memory and Memory Management Unit

Lecture 14
Bus Structure (Part 1)

Lecture 15
Bus Structure (Part 2)

Lecture 16
Bus Structure - 3 Serial Interfaces

Lecture 17
Serial Interfaces

Lecture 18
Power Aware Architecture

Lecture 19
Software for Embedded Systems

Lecture 20
Fundamentals of Embedded Operating Systems

Lecture 21
Scheduling Policies

Lecture 22
Resource Management

Lecture 23
Embedded - OS

Lecture 24
Networked Embedded System (Part 1)

Lecture 25
Networked Embedded System (Part 2)

Lecture 26
Networked Embedded System (Part 3)

Lecture 27
Networked Embedded System (Part 4)

Lecture 28
Designing Embedded Systems (Part 1)

Lecture 29
Designing Embedded Systems (Part 2)

Lecture 30
Designing Embedded Systems (Part 3)

Lecture 31
Designing Embedded Systems (Part 4)

Lecture 32
Designing Embedded Systems (Part 5)

Lecture 33
Platform-based Design

Lecture 34
Compilers for Embedded Systems

Lecture 35
Developing Embedded Systems

Lecture 36
Building Dependable Embedded Systems

Lecture 37
Pervasive & Ubiquitous Computing

Lecture 1
Introduction

Lecture 2
Architecture of Industrial Automation

Lecture 3
Measurement Systems Characteristics

Lecture 9
Signal Conditioning (Part 2)

Lecture 19
Sequence Control: Scan Cycle and Simple RLL Programs

Lecture 20
Sequence Control: More RLL Elements and RLL Syntax

Lecture 21
A Structured Design Approach to Sequence

Lecture 22
PLC Hardware Environment

Lecture 23
Introduction To CNC Machines

Lecture 24
Contour Generation and Motion Control

Lecture 25
Flow Control Valves

Lecture 36
Embedded Systems

Lecture 39
Higher Level Automation Systems

Module 1 - Lecture 2
Multi-layered Neural Networks

Module 1 - Lecture 3
Back Propagation Algorithm Revisited

Module 1 - Lecture 4
Non-linear System Analysis (Part 1)

Module 1 - Lecture 5
Non-linear System Analysis (Part 2)

Module 1 - Lecture 6
Radial Basis Function Networks

Module 1 - Lecture 7
Adaptive Learning Rate

Module 1 - Lecture 8
Weight Update Rules

Module 1 - Lecture 9
Recurrent Networks Back Propagation Through Time

Module 1 - Lecture 10
Recurrent Networks Real Time Recurrent Learning

Module 1 - Lecture 11
Self-Organizing Map - Multidimensional Networks

Module 2 - Lecture 1
Fuzzy sets - A Primer

Module 2 - Lecture 2
Fuzzy Relations

Module 2 - Lecture 3
Fuzzy Rule-base and Approximate Reasoning

Module 2 - Lecture 4
Introduction to Fuzzy Logic Control

Module 3 - Lecture 1
Neural Control: A Review

Module 3 - Lecture 3
Neural Model of a Robot Manipulator

Module 3 - Lecture 4
Indirect Adaptive Control of a Robot Manipulator

Module 3 - Lecture 5
Adaptive Neural Control for Affine Systems SISO

Module 3 - Lecture 6
Adaptive Neural Control for Affine Systems MIMO

Module 3 - Lecture 7
Visual Motor Coordination with KSOM

Module 3 - Lecture 8
Visual Motor Coordination - Quantum Clustering

Module 3 - Lecture 9
Direct Adaptive Control of Manipulators

Module 3 - Lecture 10
NN-based Back Stepping Control

Module 4 - Lecture 3
Fuzzy Control of a pH Reactor

Module 4 - Lecture 4
Fuzzy Lyapunov Controller - Computing with Words

Module 4 - Lecture 5
Controller Design for a T-S Fuzzy Model

Module 4 - Lecture 6
Linear Controllers using T-S Fuzzy Model

Lecture 1
Introduction and Course Outline

Lecture 3
Data and Signal

Lecture 4
Transmission Impairments and Channel Capacity

Lecture 7
Transmission of Digital Signal (Part 1)

Lecture 8
Transmission of Digital Signal (Part 2)

Lecture 15
Error Detection and Correction

Lecture 16
Flow and Error Control

Lecture 17
Data Link Control

Lecture 18
Switching Techniques Circuit Switching

Lecture 19
Switching Techniques Packet Switching

Lecture 20
Routing (Part 1)

Lecture 37
Audio and Video Compression

Lecture 19
CGI Scripts

Lecture 21
PERL (Part 1)

Lecture 22
PERL (Part 2)

Lecture 23
PERL (Part 3)

Lecture 24
PERL (Part 4)

Lecture 25
Javascript (Part 1)

Lecture 26
Javascript (Part 2)

Lecture 27
Using Cookies

Lecture 28
Java Applets (Part 1)

Lecture 29
Java Applets (Part 2)

Lecture 30
Client-Server Programming in Java

Lecture 32
Basic Cryptographic Concepts (Part 1)

Lecture 33
Basic Cryptographic Concepts (Part 2)

Lecture 34
Basic Cryptographic Concepts (Part 3)

Lecture 35
Electronic Commerce

Lecture 1
Introduction

Lecture 2
Overview on Modern Cryptography

Lecture 3
Introduction to Number Theory

Lecture 4
Probability and Information Theory

Lecture 5
Classical Cryptosystems

Lecture 6
Cryptanalysis of Classical Ciphers

Lecture 7
Shannons Theory (Part 1)

Lecture 8
Shannons Theory (Part 2)

Lecture 9
Symmetric Key Ciphers

Lecture 10
Block Cipher Standards (DES)

Lecture 11
Block Cipher Standards (AES) (Part 1)

Lecture 12
Block Cipher Standards (AES) (Part 2)

Lecture 13
Linear Cryptanalysis

Lecture 14
Differential Cryptanalysis

Lecture 15
Few other Cryptanalytic Techniques

Lecture 16
Overview on S-Box Design Principles

Lecture 17
Modes of Operation of Block Ciphers

Lecture 18
Stream Ciphers (Part 1)

Lecture 19
Stream Ciphers (Part 2)

Lecture 20
Stream Ciphers (Part 3)

Lecture 21
Pseudorandomness

Lecture 22
Cryptographic Hash Functions (Part 1)

Lecture 23
Cryptographic Hash Functions (Part 2)

Lecture 24
Cryptographic Hash Functions (Part 3)

Lecture 25
Message Authentication Codes

Lecture 26
More Number Theoretic Results

Lecture 27
The RSA Cryptosystem

Lecture 28
Primality Testing

Lecture 29
Factoring Algorithms

Lecture 30
Some Comments on the Security of RSA

Lecture 31
Discrete Logarithm Problem (DLP)

Lecture 32
The Diffie-Hellman Problem and Security of ElGamal Systems

Lecture 33
An Introduction to Elliptic Curve

Lecture 34
Application of Elliptic Curves to Cryptography

Lecture 35
Implementation of Elliptic Curve Cryptography

Lecture 36
Secret Sharing Schemes

Lecture 37
A Tutorial on Network Protocols

Lecture 38
System Security

Lecture 39
Firewalls and Intrusion Detection Systems

Lecture 40
Side Channel Analysis of Cryptographic Implementations

Lecture 1
Introduction & Course Outline

Lecture 2
MOS Transistors (Part 1)

Lecture 3
MOS Transistors (Part 2)

Lecture 4
MOS Transistors (Part 3)

Lecture 5
MOS Transistors (Part 4)

Lecture 6
MOS Inverters (Part 1)

Lecture 7
MOS Inverters (Part 2)

Lecture 8
MOS Inverters (Part 3)

Lecture 9
MOS Inverters (Part 4)

Lecture 10
Static CMOS Circuits (Part 1)

Lecture 11
Static CMOS Circuits (Part 2)

Lecture 12
MOS Dynamic Circuits (Part 1)

Lecture 13
MOS Dynamic Circuits (Part 2)

Lecture 14
Pass Transistor Logic Circuits (Part 1)

Lecture 15
Pass Transistor Logic Circuits (Part 2)

Lecture 16
MOS Memories

Lecture 17
Finite State Machines

Lecture 18
Switching Power Dissipation

Lecture 19
Tutorial (Part 1)

Lecture 20
Dynamic Power Dissipation

Lecture 21
Leakage Power Dissipation

Lecture 22
Supply Voltage Scaling (Part 1)

Lecture 23
Supply Voltage Scaling (Part 2)

Lecture 24
Supply Voltage Scaling (Part 3)

Lecture 25
Supply Voltage Scaling (Part 4)

Lecture 26
Tutorial (Part 2)

Lecture 27
Minimising Switched Capacitance (Part 1)

Lecture 28
Minimising Switched Capacitance (Part 2)

Lecture 29
Minimising Switched Capacitance (Part 3)

Lecture 30
Minimising Switched Capacitance (Part 4)

Lecture 31
Minimising Switched Capacitance (Part 5)

Lecture 32
Minimising Leakage Power (Part 1)

Lecture 33
Minimising Leakage Power (Part 2)

Lecture 34
Minimising Leakage Power (Part 3)

Lecture 35
Variation Tolerant Design

Lecture 36
Adiabatic Logic Circuits

Lecture 37
Battery-driven System Design

Lecture 38
CAD Tools for Low Power

Lecture 39
Tutorial (Part 3)

Lecture 40
Course Summary

Lecture 1
Introduction & Course Outline

Lecture 2
Performance

Lecture 3
Instruction Set

Lecture 4
MIPS ISA and Processor (Part 1)

Lecture 5
MIPS ISA and Processor (Part 2)

Lecture 6
Introduction to Pipelining

Lecture 7
Instruction Pipelining

Lecture 8
Pipeline Hazards

Lecture 9
Data Hazards

Lecture 10
Software Pipelining

Lecture 11
In Quest of Higher ILP (Part 1)

Lecture 12
In Quest of Higher ILP (Part 2)

Lecture 13
Dynamic Instruction Scheduling (Part 1)

Lecture 14
Dynamic Instruction Scheduling (Part 4)

Lecture 15
Control Hazards

Lecture 16
Branch Prediction (Part 1)

Lecture 17
Branch Prediction (Part 2)

Lecture 18
Dynamic Instruction

Lecture 19
Hardware-based Speculation

Lecture 20
Tutorial

Lecture 21
Hierarchical Memory Organisation (Part 1)

Lecture 22
Hierarchical Memory Organisation (Part 2)

Lecture 23
Hierarchical Memory Organisation (Part 3)

Lecture 24
Hierarchical Memory Organisation (Part 4)

Lecture 25
Cache Optimisation Techniques (Part 1)

Lecture 26
Cache Optimisation Techniques (Part 2)

Lecture 27
Main Memory Organisation

Lecture 28
Main Memory Optimisations

Lecture 29
Virtual Memory (Part 1)

Lecture 30
Virtual Memory (Part 2)

Lecture 31
Virtual Machines

Lecture 32
Storage Technology (Part 1)

Lecture 33
Storage Technology (Part 2)

Lecture 34
Case Studies (Part 1)

Lecture 35
Case Studies (Part 2)

Lecture 36
Case Studies (Part 3)

Lecture 37
Multi-threading & Multi-processing

Lecture 38
Simultaneous Multi-threading

Lecture 39
Symmetric Multiprocessors

Lecture 40
Distributed Memory Multiprocessors

Lecture 41
Cluster, Grid and Cloud Computing

Lecture 1
An Overview of a Compiler (Part 1)

Lecture 2
An Overview of a Compiler(Part 2) and Run-Time Environments(Part 1)

Lecture 3
Run-Time Environments (Part 2)

Lecture 4
Run-Time Environments (Part 3) and Local Optimisations (Part 1)

Lecture 5
Local Optimisations (Part 2)

Lecture 6
Code Generation (Part 1)

Lecture 7
Code Generation (Part 2)

Lecture 8
Code Generation (Part 3) and Global Register Allocation (Part 1)

Lecture 9
Global Register Allocation (Part 2)

Lecture 10
Global Register Allocation (Part 3) and Implementing Object-Oriented Languages (Part 1)

Lecture 11
Implementing Object-Oriented Languages (Part 2) and Introduction to Machine-Independent Optimisations (Part 1)

Lecture 12
Introduction to Machine-Independent Optimisations (Part 2) and Data-Flow Analysis (Part 1)

Lecture 13
Data-Flow Analysis (Part 2)

Lecture 14
Data-Flow Analysis (Part 3) and Control-Flow Analysis (Part 1)

Lecture 15
Control-Flow Analysis (Part 2)

Lecture 16
Machine-Independent Optimisations (Part 1)

Lecture 17
Machine-Independent Optimisations (Part 2)

Lecture 18
Machine-Independent Optimizations (Part 3) and Data-Flow Analysis: Theoretical Foundation (Part 1)

Lecture 19
Data-Flow Analysis: Theoretical Foundation (Part 2) and Partial Redundancy Elimination (Part 1)

Lecture 20
Partial Redundancy Elimination (Part 2)

Lecture 21
The Static Single Assignment Form (Part 1)

Lecture 22
The Static Single Assignment Form (Part 2)

Lecture 23
The Static Single Assignment Form (Part 3)

Lecture 24
Automatic Parallelisation (Part 1)

Lecture 25
Automatic Parallelisation (Part 2)

Lecture 26
Automatic Parallelisation (Part 3)

Lecture 27
Automatic Parallelisation (Part 4)

Lecture 28
Instruction Scheduling (Part 1)

Lecture 29
Instruction Scheduling (Part 2)

Lecture 30
Instruction Scheduling (Part 3)

Lecture 31
Software Pipelining

Lecture 32
Energy-Aware Software Systems (Part 1)

Lecture 33
Energy-Aware Software Systems (Part 2)

Lecture 34
Energy-Aware Software Systems (Part 3)

Lecture 35
Energy-Aware Software Systems (Part 4)

Lecture 36
Just-In-Time Compilation and Optimisations for .NET CLR

Lecture 37
Garbage Collection

Lecture 38
Interprocedural Data-Flow Analysis

Lecture 39
Worst Case Execution Time (Part 1)

Lecture 40
Worst Case Execution Time (Part 2)

Lecture 1
Introduction

Lecture 2
Image Digitisation (Part 1)

Lecture 3
Image Digitisation (Part 2)

Lecture 4
Pixel Relationships (Part 1)

Lecture 5
Pixel Relationships (Part 2)

Lecture 6
Basic Transformations

Lecture 7
Camera Model and Imaging Geometry

Lecture 8
Camera Calibration and Stereo Imaging

Lecture 9
Interpolation and Resampling

Lecture 10
Image Interpolation

Lecture 11
Image Transformation (Part 1)

Lecture 12
Image Transformation (Part 2)

Lecture 13
Fourier Transformation (Part 1)

Lecture 14
Fourier Transformation (Part 2)

Lecture 15
Discrete Cosine Transform

Lecture 16
K-L Transform

Lecture 17
Image Enhancement (Part 1)

Lecture 18
Image Enhancement (Part 2)

Lecture 19
Image Enhancement (Part 3)

Lecture 20
Image Enhancement (Part 4)

Lecture 21
Image Enhancement Frequency

Lecture 22
Image Restoration (Part 1)

Lecture 23
Image Restoration (Part 2)

Lecture 24
Image Restoration (Part 3)

Lecture 25
Image Registration

Lecture 26
Colour Image Processing (Part 1)

Lecture 27
Colour Image Processing (Part 2)

Lecture 28
Colour Image Processing (Part 3)

Lecture 29
Image Segmentation (Part 1)

Lecture 30
Image Segmentation (Part 2)

Lecture 31
Image Segmentation (Part 3)

Lecture 32
Image Segmentation (Part 4)

Lecture 33
Mathematical Morphology (Part 1)

Lecture 34
Mathematical Morphology (Part 2)

Lecture 35
Mathematical Morphology (Part 3)

Lecture 36
Mathematical Morphology (Part 4)

Lecture 37
Object Representation and Description (Part 1)

Lecture 38
Object Representation and Description (Part 2)

Lecture 39
Object Representation and Description (Part 3)

Lecture 40
Object Recognition

Lecture 15
Microstereolithography

Lecture 16
MEMS Microsensors Thermal Sensors

Lecture 20
MEMS Inertial Sensors

Lecture 21
Micromachined Microaccelerometers for MEMS

Lecture 22
MEMS Accelerometers for Avionics

Lecture 23
Temperature Drift and Damping Analysis

Lecture 22
Modulation Techniques for Mobile Communication (Part 2)

Lecture 33
Coding Techniques for Mobile Communications (Part 1)

Lecture 1
Introduction to Statistical Pattern Recognition

Lecture 2
Overview of Pattern Classifiers

Lecture 3
The Bayes Classifier for Minimising Risk

Lecture 4
Estimating Bayes Error, Minimax and Neymann-Pearson Classifiers

Lecture 5
Implementing Bayes Classifier and Estimation of Class Conditional Densities

Lecture 6
Maximum Likelihood Estimation of Different Densities

Lecture 7
Bayesian Estimation of Parameters of Density Functions, MAP Estimates

Lecture 8
Bayesian Estimation Examples, the Exponential Family of Densities and ML Estimates

Lecture 9
Sufficient Statistics, Recursive Formulation of ML and Bayesian Estimates

Lecture 10
Mixture Densities, ML Estimation and EM Algorithm

Lecture 11
Convergence of EM Algorithm, Overview of Nonparametric Density Estimation

Lecture 12
Nonparametric Estimation, Parzen Windows, Nearest Neighbour Methods

Lecture 13
Linear Discriminant Functions, Perceptron--Learning Algorithm and Convergence Proof

Lecture 14
Linear Discriminant Functions; Perceptron -- Learning Algorithm and Convergence Proof

Lecture 15
AdaLinE and LMS Algorithm; General Nonliner Least-squares Regression

Lecture 16
Logistic Regression, Statistics of Least Squares Method and Regularised Least Squares

Lecture 17
Fisher Linear Discriminant

Lecture 18
Linear Discriminant Functions for Multi-Class Case and Multi-Class Logistic Regression

Lecture 19
Learning and Generalisation; PAC Learning Framework

Lecture 20
Overview of Statistical Learning Theory; Empirical Risk Minimisation

Lecture 21
Consistency of Empirical Risk Minimisation

Lecture 22
Consistency of Empirical Risk Minimisation; VC-Dimension

Lecture 23
Complexity of Learning Problems and VC-Dimension

Lecture 24
VC-Dimension Examples; VC-Dimension of Hyperplanes

Lecture 25
Overview of Artificial Neural Networks

Lecture 26
Multilayer Feedforward Neural Networks with Sigmoidal Activation Functions

Lecture 27
Backpropagation Algorithm; Representational Abilities of Feedforward Networks

Lecture 28
Feedforward Networks for Classification and Regression; Backpropagation in Practice

Lecture 29
Radial Basis Function Networks; Gaussian RBF Networks

Lecture 30
Learning Weights in RBF networks; K-means Clustering Algorithm

Lecture 31
Introduction to Support Vector Machines

Lecture 32
SVM Formulation with Slack Variables; Non-linear SVM Classifiers

Lecture 33
Kernel Functions for Non-linear SVMs; Mercer and Positive Definite Kernels

Lecture 34
Support Vector Regression and Examples of SVM Learning

Lecture 35
Overview of SMO and Other Algorithms for SVM

Lecture 36
Positive Definite Kernels, RKHS and Representer Theorem

Lecture 37
Feature Selection and Dimensionality Reduction; Principal Component Analysis

Lecture 38
No Free Lunch Theorem; Model Selection and Estimation; Bias-variance Trade-off

Lecture 39
Assessing Learnt Classifiers; Cross Validation

Lecture 40
Bootstrap; Bagging and Boosting; Classifier Ensembles; AdaBoost

Lecture 41
Risk Minimisation View of AdaBoost

Lecture 1
Introduction

Lecture 2
Propositional Logic Syntax

Lecture 3
Semantics of Propositional Logic

Lecture 4
Logical and Algebraic Concepts

Lecture 5
Identities and Normal Forms

Lecture 6
Tautology Checking

Lecture 7
Propositional Unsatisfiability

Lecture 8
Analytic Tableaux

Lecture 9
Consistency and Completeness

Lecture 10
The Completeness Theorem

Lecture 11
Maximally Consistent Sets

Lecture 12
Formal Theories

Lecture 13
Proof Theory - Hilbert-style

Lecture 14
Derived Rules

Lecture 15
The Hilbert System - Soundness

Lecture 16
The Hilbert System - Completeness

Lecture 17
Introduction to Predicate Logic

Lecture 18
The Semantic of Predicate Logic

Lecture 19
Substitutions

Lecture 20
Models

Lecture 21
Structures and Substructures

Lecture 22 -
First-order Theories

Lecture 23
Predicate Logic: Proof Theory

Lecture 24
Existential Quantification

Lecture 25
Normal Forms

Lecture 26
Skolemisation

Lecture 27
Substitutions and Instantiations

Lecture 28
Unification

Lecture 29
Resolution in FOL

Lecture 30
More on Resolution in FOL

Lecture 31
Resolution - Soundness and Completeness

Lecture 32
Resolution and Tableaux

Lecture 33
Completeness of Tableaux Method

Lecture 34
Completeness of the Hilbert System

Lecture 35
First Order Theories

Lecture 36
Towards Logic Programming

Lecture 37
Verification of Imperative Programs

Lecture 38
Verification of WHILE Programs

Lecture 39
References

Lecture 1
Introduction to Biometrics

Lecture 2
Basic Image Processing Algorithms

Lecture 3
Geometric Image Transformation

Lecture 4
Basic Image Processing Operations

Lecture 5
Spatial Filtering

Lecture 6
Edge Detection

Lecture 7
Canny Edge Detection

Lecture 8
Security System

Lecture 9
Principal Component Analysis

Lecture 10
Biometric Identifiers

Lecture 11
Problem Statement for Verification

Lecture 12
Basic System Errors

Lecture 13
ROC Curves

Lecture 14
Selection of a Biometric

Lecture 15
Multimodal Scheme Verification

Lecture 16
Vulnerabilities of Biometric System

Lecture 17
Offline Signature Verification

Lecture 18
Discrete Haar Wavelet Transform

Lecture 19
Fingerprint System

Lecture 20
Ear Biometrics System

Lecture 21
Multimodal Biometrics Projects

Lecture 22
Iris Recognition

Lecture 23
Finger Knuckle Print ROI Extraction

Lecture 24
Nose Tip Detection

Lecture 25
Finger Knuckle Print Recognition

Lecture 26
Automatic Nose Tip Detection

Lecture 1
Introduction

Lecture 2
Parallel Programming Paradigms

Lecture 3
Parallel Architecture (Part 1)

Lecture 4
Parallel Architecture (Part 2)

Lecture 5
Open MP (Part 1)

Lecture 6
Open MP (Part 2)

Lecture 7
Open MP (Part 3)

Lecture 8
Open MP & PRAM Model of Computation

Lecture 9
PRAM

Lecture 10
Models of Parallel Computation, Complexity

Lecture 11
Memory Consistency

Lecture 12
Memory Consistency & Performance Issues

Lecture 13
Parallel Program Design

Lecture 14
Shared Memory and Message Passing

Lecture 15
MPI (Part 1)

Lecture 16
MPI (Part 2)

Lecture 17
MPI (Part 3)

Lecture 18
Algorithmic Techniques (Part 1)

Lecture 19
Algorithmic Techniques (Part 2)

Lecture 20
Algorithmic Techniques (Part 3)

Lecture 21
CUDA (Part 1)

Lecture 22
CUDA (Part 2)

Lecture 23
CUDA (Part 3)

Lecture 24
CUDA (Part 4)

Lecture 25
CUDA (Part 5)

Lecture 26
CUDA (Part 6)

Lecture 27
CUDA (Part 7)

Lecture 28
Algorithms, Merging & Sorting (Part 1)

Lecture 29
Algorithms, Merging & Sorting (Part 2)

Lecture 30
Algorithms, Merging & Sorting (Part 3)

Lecture 31
Algorithms, Merging & Sorting (Part 4)

Lecture 32
Algorithms, Merging & Sorting (Part 5)

Lecture 33
Lower Bounds Lock Free Synchronization, Load Stealing

Lecture 34
Lock Free Synchronization, Graph Algorithms

Lecture 1
Introduction to Data Structures and Algorithms

Lecture 2
Stacks

Lecture 3
Queues and Linked Lists

Lecture 4
Dictionaries

Lecture 5
Hashing

Lecture 6
Trees

Lecture 7
Tree Walks / Traversals

Lecture 8
Ordered Dictionaries

Lecture 9
Deletion

Lecture 10
Quick Sort

Lecture 11
AVL Trees (Part 1)

Lecture 12
AVL Trees (Part 2)

Lecture 13
Trees

Lecture 14
Red Black Trees

Lecture 15
Insertion in Red Black Trees

Lecture 16
Disk Based Data Structures

Lecture 17
Case Study: Searching for Patterns

Lecture 18
Tries

Lecture 19
Data Compression

Lecture 20
Priority Queues

Lecture 21
Binary Heaps

Lecture 22
Why Sorting

Lecture 23
More Sorting

Lecture 24
Graphs

Lecture 25
Data Structures for Graphs

Lecture 26
Two Applications of Breadth First Search

Lecture 27
Depth First Search

Lecture 28
Applications of DFS

Lecture 29
DFS in Directed Graphs

Lecture 30
Applications of DFS in Directed Graphs

Lecture 31
Minimum Spanning Trees

Lecture 32
The Union

Lecture 33
Prims Algorithm for Minimum Spanning Trees

Lecture 34
Single Source Shortest Paths

Lecture 35
Correctness of Dijkstras Algorithm

Lecture 36
Single Source Shortest Paths

Lecture 1
Introduction

Lecture 2
Real Time System Characteristics

Lecture 3
Few Basic Issues

Lecture 4
Modelling Timing Constraints (Part 1)

Lecture 5
Modelling Timing Constraints (Part 2)

Lecture 6
Basics of Real Time Task Scheduling

Lecture 7
Cyclic Scheduler

Lecture 9
Rate Monotonic Scheduler

Lecture 10
RMA Scheduling : Further Issues

Lecture 11
Deadline Monotonic Scheduling and Other Issues

Lecture 12
Few Issues in Use of RMA

Lecture 13
Resource Sharing Among Real-Time Tasks

Lecture 8
Event-driven Scheduling

Lecture 14
Highest Locker and Priority Ceiling Protocols

Lecture 15
An Analysis of Priority Ceiling Protocol

Lecture 16
Handling Task Dependencies

Lecture 17
Real-Time Task Scheduling on Multiprocessors and Distributed Systems (Part 1)

Lecture 18
Real-Time Task Scheduling on Multiprocessors and Distributed Systems (Part 2)

Lecture 19
Clock Synchronisation in Distributed Real-Time Systems

Lecture 20
Internal Clock Synchronisation in Presence of Byzantine Clocks

Lecture 21
A Few Basic Issues in Real-Time Operating Systems (Part 1)

Lecture 22
Tutorial

Lecture 23
A Few Basic Issues in Real-Time Operating Systems (Part 2)

Lecture 24
Unix and Windows as RTOS

Lecture 25
Real-Time POSIX (Part 1)

Lecture 26
Real-Time POSIX (Part 2)

Lecture 27
Open Source and Commercial RTOS (Part 1)

Lecture 28
Open Source and Commercial RTOS (Part 2)

Lecture 29
Benchmarking Real - Time Computer & Operating Systems (Part 1)

Lecture 30
Benchmarking Real - Time Computer & Operating Systems (Part 2)

Lecture 31
Real - Time Communications

Lecture 32
Few Basic Issues in Real - Time Communications

Lecture 33
Review of Computer Networking

Lecture 34
Real - Time Communication in a LAN (Part 1)

Lecture 35
Real - Time Communication in a LAN (Part 2)

Lecture 36
Performance of Two Real -Time Communication Protocols

Lecture 37
Real - Time Communication over Packet Switched Networks (Part 1)

Lecture 38
Real - Time Communication over Packet Switched Networks (Part 2)

Lecture 39
Real - Time Communication over Packet Switched Networks (Part 3)

Lecture 40
Real - Time Databases

Lecture 17
User-Memory-CPU Interactions

Lecture 21
Data Structures

Lecture 22
Abstractions

Lecture 39
GFS

Lecture 40
GFS Model

Lecture 42
GFS Problems, BigTable

Lecture 43
Lessons to learn

Lecture 1
Introduction

Lecture 2
Matchings: Konig’s theorem and Hall’s theorem

Lecture 3
More on Hall’s theorem and some applications

Lecture 4
Tutte’s theorem on existence of a perfect matching

Lecture 6
More on Matchings

Lecture 7
Dominating set, path cover

Lecture 8
Gallai-Millgram theorem, Dilworth’s theorem

Lecture 9
Connectivity

Lecture 10
Menger’s theorem

Lecture 5
More on Tutte’s theorem

Lecture 11
More on connectivity

Lecture 12
Minors, topological minors and more on k-linkedness

Lecture 13
Vertex colouring

Lecture 14
More on vertex colouring

Lecture 15
Edge coloring: Vizing’s theorem

Lecture 16
Proof of Vizing’s theorem, Introduction to planarity

Lecture 17
Five-coloring planar graphs, Kuratowsky’s theorem

Lecture 18
Proof of Kuratowsky’s theorem, List coloring

Lecture 19
List chromatic index

Lecture 20
Adjacency polynomial of a graph and combinatorial Nullstellensatz

Lecture 21
Chromatic polynomial, k-critical graphs

Lecture 22
Gallai-Roy theorem, Acyclic coloring, Hadwiger’s conjecture

Lecture 23
Perfect graphs

Lecture 24
Interval graphs, chordal graphs

Lecture 25
Proof of weak perfect graph theorem

Lecture 26
Second proof of WPGT

Lecture 27
More special classes of graphs

Lecture 28
Boxicity, Sphericity, Hamiltonian circuits

Lecture 29
More on Hamiltonicity: Chvatal’s theorem

Lecture 30
Chvatal’s theorem

Lecture 31
Network flows

Lecture 32
More on network flows

Lecture 33
More on circulations and tensions

Lecture 34
Flow number and Tutte’s flow conjectures

Lecture 35
Random graphs and probabilistic method

Lecture 36
Probabilistic method (Part 1)

Lecture 37
Probabilistic method (Part 2)

Lecture 38
Probabilistic method (Part 3)

Lecture 39
Graph minors and Hadwiger’s conjecture

Lecture 40
More on graph minors, tree decompositions

Lecture 1
Course introduction

Lecture 2
Negative feedback amplifier

Lecture 3
Step response, sinusoidal steady state response

Lecture 4
Loop gain and unity loop gain frequency

Lecture 5
Op amp realisation using controlled sources

Lecture 6
Negative feedback amplifier with ideal delay-small delays

Lecture 7
Negative feedback amplifier with ideal delay-large delays

Lecture 8
Negative feedback amplifier with parasitic poles and zeroes

Lecture 9
Negative feedback amplifier with parasitic poles and zeros

Lecture 30
Differential pair with current mirror load

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