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Introduction to DSP
- 1. Prepared by Ms.J.Shiny Christobel AssistantProfessor Department of ECE Sri Ramakrishna Institute of Technology, Coimbatore 1
- 2. Introduction toDSP Block Diagram Filters Applications 2
- 3. SIGNAL A physicalquantity varies with time, space or any other independent variable 1-D (Eg: Speech , ECG or EEG signal) 2-D (Eg: Image) 3-D (Eg:Videos) Multi dimensional signal(Eg:Google map) 3
- 4. Analog Signal Signalthat are not digitalized Denoted by x(t) Analog signal = continuous-time + continuous amplitude Eg: Audio, Inputs through microphone 4
- 5. Discrete Signal Signalthat are digitalized Denoted by x(n) Discrete signal = Discrete-time + Discrete amplitude Digital signal -quantization of the discrete signal 5
- 6. Energy signal(E=finite and P=infinity) Power signal (E=0 and P=finite) Causal signal (depends on past and present values) Non-causal signal (depends on future values) Deterministic signal (Eg: CT or DT signal) Random signal (Eg: Noise) 6
- 7. Analysis ,interpretation and manipulation of signals Gets an input signal, process it and produces an output signal. 7
- 8. When asignal is transmitted from one point to another there is every possibility of contamination /deformation of the signal by external noise. So to retrieve the original signal at the receiver suitable filters are to be used. 8
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- 10. A systemis any process that produces an output signal in response to an input signal Continuous systems-input and output are continuous signals, such as in analog electronics Discrete systems-input and output are discrete signals Eg: computer programs that manipulate the values stored in arrays. 10
- 11. Static orDynamic system Linear and Non-linear system (superposition principle) Time Varient and time In-varient system Causal and non-causal systems Stable and unstable system 11
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- 14. USES OF FILTERS(Eg:Poor audio, Blurred Image) Signal restoration Signal separation TYPES OF FILTERS 14
- 15. Analog filterstake the analog signal as input and process the signal and finally gives the analog output. An analog filter is constructed using resistors, capacitors, active components etc… An analog filter is denoted by a differential equation. (Laplace tranform) 15
- 16. 16 A digitalfilter processes and generates digital data. (Z-Transform) A digital filter constitutes elements like adder, multiplier and delay units. Digital filters are vastly superior in the level of performance in comparison to analog filters.
- 17. A digitalfilter is denoted by a difference equation The performance is not influenced by component ageing, temperature and power variations. It is highly immune to noise and relatively stable. Transportation and reconfiguration is very easy which is not true in the case of analog filters. Multiple filtering is possible only in digital filters. Computational problems are minimum. 17
- 18. Quantization erroroccurs due to finite word length in the representation of signals and parameters. Digital filters also suffer from Bandwidth problems. 18
- 19. FIR Filters(Finite impulse response filters) IIR Filters (Infinite Impulse response filters) 19
- 20. The digitalfilter whose impulse response is of finite duration is known as Finite impulse response filter The response depends only on the present and past input samples Also called non recursive filters It has a finite number of non-zero terms FIR filters can be designed with exact linear phase. FIR filters are stable Round off noise can be eliminated in FIR filters DEMERT :The delay of linear phase FIR filters can create problems in some DSP applications. 20
- 21. The digitalfilter whose impulse response is of infinite duration is known as Infinite impulse response filter. The response of an IIR filter is a function of current and past input signal samples and past output signal samples. It is also called recursive filter. It has lesser number of side lobes in the stop- band. The implementation of an IIR filter involves fewer parameters, less memory requirements and lower computational complexity 21
- 22. IIR filtersdo not have linear phase not very stable Realization of IIR filters is not very easy as compared to FIR filters As it is a recursive filter the number of coefficients is very large and the memory requirements are also high 22
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- 24. In allmusical recordings, the sound from instruments is recorded in studio and then special audio effects are added by manipulating the recorded musical sounds. The audio effects are artificially generated using various DSP techniques. the sound recorded in a studio is different and it doesn’t sound natural. So, echoes are simply generated by delay units. The direct sound and a single echo appear in K sampling period latter can be generated by the FIR filter with the system function 24
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- 26. To generatemultiple echoes separated K sampling periods we can use an FIR filter with transfer function 26
- 27. The otherspecial sound effects are flanging and chorus. The flanging effect is created by feeding the same musical note to two tape recorders and then combining their delayed outputs. This effect can be simulated using the FIR filter by periodically varying the delay K(n) between 0 and K. 27
- 28. The choruseffect is achieved when several musicians are playing the same musical note at the same time with small changes in the amplitudes and small timing differences between their sounds. A chorus generator can be realized by parallelly connecting few number of flanging effect filters 28
- 29. IMAGE PROCESSING CancerDetection Fog Removal SPEECH PROCESSING Speech to Text conversion 29
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