Course Highlights:

An Embedded System can be defined as a Software System that is completely encapsulated by the hardware it controls. The term embedded system is a nebulous one that encompasses just about everything except desktop PCs. An embedded system is one that is preprogrammed to perform a dedicated set of functions or operations. Historically, embedded systems have been predominantly automation and control systems like the Aircraft Control Systems, Satellite Control Systems, and Industrial Automation & Control Systems etc. But nowadays, embedded systems have emerged as an integral part of the society.  Majority of the Hi-Tech Gadgets like a PDA, Mobile Phone, Pager, Digital Wrist Watch, Calculator, Cordless Telephone, Digital Answering M/C, MP3 Player, Disc Man, Digital Video Camera etc, are all products of the class “embedded systems”.

Embedded Systems typically have tight constraints on both functionality and implementation. In particular, they must guarantee real time operations reactive to external events, conform to size and weight limits, budget, power and cooling consumption, satisfy safety and reliability requirements, and meet tight cost targets. Discussed below are the issues and challenges for an Embedded Products in general and Embedded System Designer in particular.

Thus an embedded system is a specialized computer system that is integrated as part of a larger system. Many embedded systems are implemented using digital signal processors. The DSP will interface with the other embedded components to perform a specific function. The specific embedded application will determine the specific DSP to be used. For example, if the embedded application is one that performs video processing, the system designer may choose a DSP that is customized to perform media processing, including video and audio processing.

Signal processing is here to stay. It’s everywhere. Any time you have a signal that need to be understood and interpreted properly, it needs to be processed. The digital part is just the process of making it all work on a computer of some sort. If it’s an embedded application you must do this with the minimal amount of resources possible. Everything costs money; cycles, memory, power—so everything must be conserved. This is the nature of embedded computing; be application specific, tailor to the job at hand, reduce cost as much as possible, and make things as efficient as possible.

This course covers concepts of embedded system design using a DSP processor. This course provides detailed analysis of the embedded system development in the DSP applications by examining the basic steps such as examining the overall needs of the system; selecting the hardware components required for the system, understanding DSP basics and architecture. This course also provides insight into the resource allocation and its constraints and also the run time performance of an algorithm on the DSP processor by describing the optimization procedures.

This course also covers the RTOS for DSP, testing and debugging of DSP systems.

Objectives of the course:

Developing embedded Digital Signal Processing (DSP) applications is a complex task influenced by many parameters. But by using a systematic approach the result can be an efficient implementation. This course provides an overview of application development techniques associated with DSPs in embedded systems. Topics include differences between DSPs and other general purpose processors, choosing a DSP for an embedded application, survey of DSP architectures, optimization and benchmarking techniques for DSP, and a summary of tools for DSP application development and real-time application development techniques using DSPs.

Who Should Attend:

DSP professionals, graduates and research scholars who would like to know profound aspects real time embedded system design aspects using DSP processors such as:

• DSP Systems as Hard Real-Time Systems
• Components and Characteristics of a typical Embedded System
• The Embedded System Life Cycle using DSP
• Hardware Implementation for DSP algorithms
• DSP Architecture Optimization for Filter Implementation
• Pipelined Processing
• Resource Conflicts
• Specialized Instructions and Addressing  Modes
• Software Pipelining for optimizing DSP implementation
• Power Optimization techniques in DSP Devices
• Real Time Operating Systems for DSP
Course Outline:

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