Digital Signal Processing (DSP) involves the manipulation of digital signals for various applications, including biomedical diagnostics, speech recognition, telecommunications, and image processing. It leverages specialized DSP chips for efficient computation and employs both analog-to-digital and digital-to-analog conversions to handle signals. While DSP has advantages over analog systems, such as better accuracy and flexibility, it faces limitations like information loss and aliasing due to the nature of sampled signals.
Dhaka International University Whatis Digital Signal Processing (DSP)? Digital: Operating by the use of discrete signals to represent data in the form of numbers. Signal: A parameter (Electrical quantity or effect) that can be varied in such a way as to convey information. Processing: A series operations performed according to programmed instructions. Changing or analyzing information which is measured as discrete sequences of numbers. 2
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Dhaka International University Applicationof DSP-Biomedical Biomedical: Analysis of biomedical signals, diagnosis, patient monitoring, preventive health care, artificial organs. Examples: 1) Electrocardiogram (ECG) signal-provides doctor with information about the condition of the patient heart. 2) Electroencephalogram (EEG) signals- provides information about the activity of the brain 3
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Dhaka International University Applicationof DSP-Speech Speech Applications Examples: 1. Noise reduction-reducing background noise in the sequence produced by a sensing device (Microphone) 2. Speech recognition-differentiating between various speech sounds. 3. Synthesis of artificial speech- text to speech system for blind. 4
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Dhaka International University Applicationof DSP-Communications Examples: 1. Telephony- transmission of information digital form via telephones line, modem technology, mobile phones. 2. Encoding and decoding of the information sent over a physical channel (to optimize transmission or to detect or correct errors in transmission) 5
Dhaka International University Applicationof DSP-Image Processing Examples: 1. Content based image retrieval- browsing, searching and retrieving images from database. 2. Image enhancement 3. Compression- reducing the redundancy in the image data to optimize transmission/storage 7
Dhaka International University DSPImplementation To Implement DSP we must be able to 1) Perform Numerical operations including for example additions, multiplications, data transfers and logical operations Either using computer or special-purpose hardware 10
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Dhaka International University DSPChips Introduction of microprocessor in the late 1970’s and early 1980’s meant DSP techniques could be used in a much wider range of applications. DSP chip- a programmable device with its own native instruction code. Designed specifically to meet numerically-intensive requirements of DSP Capable of carrying out millions of floating point operatiopns per Second. 11
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Dhaka International University DSPImplementation- Digital/Analog Conversion To Implement DSP we must be able to Convert the digital information, after being processed back to an analog signal - involves digital to analog conversion & reconstruction e.g- text-to-speech signal (characters are used to generated artificial sound). 12
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Dhaka International University DSPImplementation- Analog/Digital Conversion To Implement DSP we must be able to Convert analog signals into the digital information - sampling & involves analog-to-digital conversion e.g- touchtone system of telephone dialing (when button is pushed two sinusoid signals are generated (tones) and transmitted, a digital system determines the frequencies and uniquely identifies the button – digital (1 to 12) output. 13
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Dhaka International University DSPImplementation To Implement DSP we must be able to Perform both A/D and D/A Conversions e.g- digital recording and playbackn of music (Signal is sensed by microphones, amplified, converted to digital, processed, and converted back to analog to be played. 14
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Dhaka International University Limitationsof DSP Most signal are analog in nature and have to be sampled Loss of information We only take samples of signals at intervals and don’t know what happens in between. Aliasing Can’t distinguish between higher and lower frequencies. Sampling Theorem: to avoid aliasing sampling rate must be at least twice the maximum frequency component (bandwidth) of signal 15
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Dhaka International University Limitationsof DSP Most signal are analog in nature and have to be sampled Limited frequency resolution We only take samples for a limited period of time does not pick up “relatively” slow changes. 16
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Dhaka International University Advantagesof Digital over Analog Signal Processing Why we Still do it? • Digital system can be simply reprogrammed for other applications/ported to different hardware/duplicated (Reconfiguring Analog system means hardware redesign, testing, verification) • DSP provides better control of accuracy requirements (Analog system depends on strict components tolerance, response may drift with temperature) • Digital signals can be easily stored without deterioration (Analog Signal are not easily transporable and often can’t be processed offline) 17
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Dhaka International University Advantagesof Digital over Analog Signal Processing Why we Still do it? • More Sophisticated signal processing algorithms can be implemented (Difficult to perform precise mathematical operations in analog form) 18
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Dhaka International University References [1].https://www.slideshare.net/op205/3f3-digital-signal-processing-part1- presentation?qid=1e6d960a-6a40-46b5-ae7a-2cc4d8764ccc&v=&b=&from_search=11 [2]. https://en.wikipedia.org/wiki/Digital_signal_processor [3]. http://www.polytechnichub.com/advantages-disadvantages-digital-signal-processor- dsp/ 19