Digital signal processing is the technique of performing mathematical operations on signals represented as a sequence of samples. These sequences are obtained by converting real-world analog signals by means of analog to digital converters. After processing, the digital samples are converted back to analog signals by means of digital to analog converters. Digital processing of signals offers many advantages over analog processing.

Examples of DSP systems:

The examples of DSP systems can be found in speech and audio systems, telecommunication applications such as modems, electronic and biomedical instrumentation, image processing, robotics, etc….

Block diagram of DSP system:

The DSP system consists of a DSP processor between the analog front end and analog back end. The analog front end consists of an anti-aliasing filter, a sample and hold circuit and an analog to digital converter feeding into DSP. The back end consists of a digital to analog converter to convert the digital output to its analog value followed by reconstruction filiter.. http://Www.blockdiagram of DSP system

Programmable digital signal processors:

A programmable digital signal processor is cost-effective. It can be programmed for different applications and has a short design n cycle time. Basically,It is a microprocessor whose architecture is optimized to process sampled data at high rates. It performs such operations as accumulating the sum of multiple products much faster than an ordinary microprocessor.

Major features of programmable digital signal processors:

1.Multiple – accumulate hardware: Multiple – accumulate is the most frequently used operation in digital signal processing. In order to implement this efficiency, the DSP has a hardware multiplier, an accumulator with an adequate number of bits to hold the sum of products, and an explicit multiply-accumulate instruction.

2.Harvard architecture: In Harvard memory architecture, there are two memory spaces, typically partitioned as program memory data memory.

3.Zero-overhead looping: The term Zero overhead looping means that the processor can execute loops without consuming cycles to test the value of the loop counter.

4.Specialized addressing: Dsp processors support specialized addressing modes that are useful for common signal processing operations and algorithms.

Important terms in designing and implementing DSP system:

  • The complexity of the algorithm: The arithmetic operations to be performed and the precision required is decided by the application.
  • Sample rate: The rate at which input samples are received and processed varies with the application, and this rate along with algorithms complexity determines whether a particular Dsp is suitable for the application.
  • Speed: Speed depends on technology.
  • Data Representation: The format and the number of bits used for data representation depending on the arithmetic precision and the dynamic range required for the given application.

The sampling process:

The process of converting an analog signal to a digital signal involves sampling the signal, holding it for conversion, and converting it to the corresponding digital value.

Aliasing :

It is the phenomenon due to which a high-frequency signal when sampled using a low sampling rate becomes a low-frequency signal that may interface with the signal of interest.

This is a preamble of DSP systems…