Real-time Digital Signal Processing Digital Filters.

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Presentation transcript:

Real-time Digital Signal Processing Digital Filters

Filters Background:. Filters may be classified as either digital or analog. Digital filters. Digital filters are implemented using a digital computer or special purpose digital hardware. Analog filters. Analog filters may be classified as either passive or active and are usually implemented with R, L, and C components and operational amplifiers.

Filters Background: active filter. An active filter is one that, along with R, L, and C components, also contains an energy source, such as that derived from an operational amplifier. passive filter. A passive filter is one that contains only R, L, and C components. It is not necessary that all three be present. L is often omitted (on purpose) from passive filter design because of the size and cost of inductors – and they also carry along an R that must be included in the design.

Passive Analog Filters Background: Four types of filters - “Ideal” lowpasshighpass bandpassbandstop

Background: Realistic Filters: lowpasshighpass bandpassbandstop Passive Analog Filters

Digital Signal Processing Basics A basic DSP system is composed of: An ADC providing digital samples of an analog input A Digital Processing system ( μ P/ASIC/FPGA) A DAC converting processed samples to analog output Real-time signal processing: All processing operation must be complete between two consecutive samples

ADC and Sampling An ADC performs the following: Sampling Quantization Binary Coding Sampling rate must be at least twice as much as the highest frequency component of the analog input signal

The z transform Discrete equivalent of the Laplace transform

z-transform properties Linear Shift theorem Note:

Transfer Function z-transform of the output/z transfer of the input Pole-zero form

Pole-zero plot

System Stability Position of the poles affects system stability The position of zeroes does not

Problem1 A system is described by the following equation: y(n)=0.5x(n) + 0.2x(n-1) + 0.1y(n-1) Plot the system’s transfer function on the z plane Is the system stable?

The Discrete Fourier Transform (DFT) Discrete equivalent of the continuous Fourier Transform A mathematical procedure used to determine the harmonic, or frequency, content of a discrete signal sequence The Fast Fourier Transform (FFT) FFT is not an approximation of the DFT, it gives precisely the same result

Digital Filtering In signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range Digital Filter: Input: Digitized samples of analog input (requires ADC) Components: Digital processor (PC/DSP/ASIC/FPGA) Output: Filtered samples (requires DAC) Applications: noise reduction, video signal enhancement, graphic equalisers

Ideal Filter Frequency Response

Realistic vs. Ideal Filter Response

FIR filtering Finite Impulse Response (FIR) filters use past input samples only Example: y(n)=0.1x(n)+0.25x(n-1)+0.2x(n-2) Z-transform: Y(z)=0.1X(z)+0.25X(z)z^(-1)+0.2X(z)(z^-2) Transfer function: H(z)=Y(z)/X(z)= z^(- 1)+0.2(z^-2) No poles, just zeroes. FIR is stable

FIR Filter Implementation y(n)=h(0)x(n)+h(1)x(n-1)+h(2)x(n-2)+h(3)x(n-3)

Example 2 A filter is described by the following equation: y(n)=0.5x(n) + 1x(n-1) + 0.5x(n-2), with initial condition y(-1) = 0 What kind of filter is it? Plot the filter’s transfer function on the z plane Is the filter stable? Plot the filter’s Implementation.

IIR Filtering Infinite Impulse Response (IIR) filters use past outputs together with past inputs

IIR Filter Implementation y(n)=b(0)x(n)+b(1)x(n-1)+b(2)x(n-2)+b(3)x(n-3) + a(0)y(n)+a(1)y(n-1)+a(2)y(n-2)+a(3)y(n-3)

FIR - IIR filter comparison FIR Simpler to design Inherently stable Require lower bit precision IIR Can simulate analog filters

Example 3 A filter is described by the following equation: y(n)=0.5x(n) + 0.2x(n-1) + 0.5y(n-1) + 0.2y(n-2), with initial condition y(-1)=y(-2) = 0 What kind of filter is it? Plot the filter’s transfer function on the z plane Is the filter stable? Plot the filter’s Implementation.