Date post: | 01-Dec-2015 |
Category: |
Documents |
Upload: | shalin-doshi |
View: | 39 times |
Download: | 0 times |
DSP and Filters
Prof. Nagendra GajjarAssistant Professor
Electronics & Communication Engineering Department
Nirma University, Ahmedabad
Agenda Introduction to DSP
Applications Digital Signals and Processing Block Diagram Advantages Disadvantages
DSP Systems
Filters Classifications Analog Filters Digital Filters Design of Digital Filters
Introduction to DSP
Applications Digital Signals and Processing Block Diagram Advantages Disadvantages
Digital Signal Processing
Digital Signal Processing means Processing signals in digital domain, which includes Modifying signal characteristics Multiplying two signals( Modulation, correlation
etc) Filtering Averaging etc..
DSP can extract one signal from another DSP can analyze a signal to extract the
characteristics
Digital Signal Processing
Applications of DSP
Space -- Remote Sensing-- Space photograph enhancement
Medicine -- Diagnostic Imaging-- EEG,ECG, Patient Monitoring
Communication-- Voice and Data Compression – Signal Multiplexing -- Filtering, Telecommunication
Defense
-- RADAR , SONAR -- Secure Communication,
-- Missile Guidance
Applications of DSP ( Contd..)
Speech Audio --Speech Recognition / Synthesis-- TTS, Digital Audio
Image Processing
--Robotic Vision
-- Animation, Image Recognition
Instrumentation / Control
-- Spectrum Analysis – Position and Rate Control -- Noise Reduction, Automotive Applications
Consumer Applications
--Digital, Cellular Mobile Phoes, Digital TVs, Digital Cameras, Voice Mail Systems, Active Suspension in the cars
Signals
DSP Systems(LTI)
Signal Transforms
System Transforms
Filter Design
Qunatization
Advanced Topics
Signals
Analog Signal x = f(t) Continuous function of independent variable Present at each and every instant of time
Digital Signal x[n]=f(nT) , T Sampling Interval Discrete function of time Present at discrete interval of time ( sampling
period)
Discrete signal Continuous signal
Converter
Sampling
These are numbers indicating amplitude at that instant.
Sample Signals
Types of Signals
Continuous Signals and Discrete Signals Analog Signals and Digital Signals Periodic Signal and Aperiodic Signals Natural Signals and Synthetic Signals 1-D, 2-D, Multi Dimensional Signals Multi Channel Signals Deterministic and Random Signals Real Valued and Complex Valued Signals Scalar and Vector Signals
Signals
Basic Digital Signals
Impulse Signal Step Signal Ramp Signal Exponential Signal
Sinusoidal Signal
Block Diagram of DSP System
Digital Processing
ADC DAC
Analog Filter Analog Filter( Antialias Filter ) ( Reconstruction
Filter )
Components of DSP system
Components of DSP System
Components of DSP System
Another Example
Basic DSP operations
Addition Subtraction Delay Multiplication
Key DSP operations
ConvolutionY(n) = Σk x(k) h(n-k)
Correlation Filtering Multiplexing Demultiplexing Modulation Demodulation Transforms
Filtering
Filtering
Modulation - DeModulation
Advantages of DSP
High Performance Guaranteed Accuracy Stability Uniformity
High Reliability Time and Temp have no effect
Flexibility Software Controlled
Time sharing of Components
Advantages of DSP ( Contd..)
No loading of Circuit Exact Linear Phase Multirate Signal Processing Easy Storage for large amount of data Very Low frequency Processing Reconfigurable Processing
Disadvantages of DSP
Speed and Cost ADC/ DAC Frequency Range
Design Time Increased Complexity Knowledge of DSP techniques
Power Dissipation Finite word length problems
DSP- When to use ?
Real Time Processing ( Processing completed within the sampling duration)
Pseudo Real-time Processing Off-Line Processing
Sampling Duration T
T= 1/f
Digitization of Analog Signals
Sampling Lossless Process Done at Nyquist Rate
Quantization Lossy Process More nits improve resolution and reduce
quantization noise
DSP Systems
“A system is defined as a process that produces an output signal in response to an input signal.”
SYSTEM
x[n] y[n]
System Response of OPAMP
system, in which the required information is stored, either as IMPULSE Response, FREQUENCY Response, or the Coefficients of the systems equation.
VinVout
BLACK BOX
Types of systems
.
CONTINUOUS TIME SYSTEM
DISCRETE TIME SYSTEM
••••••
•••
••••
•••
X(t) Y(t)
X(n) Y(n)
Values defined at all points
Values defined only at certain points values in between are not defined.
Systems are basically divided in two categories. CONTINUOUS TIME SYSTEMS. DISCRETE TIME SYSTEMS.
System Characteristics
Linearity Super Position Homogeneous
Time Invariance Causality Stability
Such Systems are called as LTI- Causal Systems
Digital System Equation
Recursive System Output of the system depends upon the
current input and its weighed previous input as well as its weighted previous outputs
Closed Loop systems Non Recursive Systems
Output of the system depends upon the current input and its weighed previous input
Open Loop systems Always Stable
Types of Digital Systems
FIR – Finite Impulse Response Filter IIR – Infinite Impulse Response Filter
Filters
An electrical device which retains certain frequency components and rejects certain frequency components
It amplifies/attenuates certain frequency components
Frequency
Magnitude
0
Classification of FiltersBased on Frequency Characteristics Low Pass Filter High Pass Filter Band Pass Filter Band Reject Filter Notch Filter Multi Pass filter ( Comb Filter )
Filter Specifications
Pass Band Frequency Stopband Frequency Passband Ripple Stopband Ripple Sampling Frequency
Computation of Order
N= -10 log(delp * dels) -15 + 1
14[ ( ws –wp)/2 *pi ]
In MATLAB
Fir1 :
In MATLAB: fir2
Fir2 : FIR arbitrary filter design using the frequency sampling method
B=fir2(N,F,am,NPT,window) N- Order of the Filter F- Frequency sampling Points A- Amplitude NPT, No of Points for frequency response Window : Type of window
Analog Filter Design
FIR Advantages
Linear Phase Multi band is possible Simple structure Always stable and no limit cycle Easy to get high speed and pipeline design Low coefficient arithmetic and round off error
and well defined quantization noise
FIR Disadvantages
Recursive FIR may be unstalbe because of imperfact pole/zero annihilation
High Filter length/ order requires high implementation cost
IIR Advantages
Standard Design using analog prototpyes Highly selective filter using low order design Design using tables and pocket calculators Good tolerance scheme Closed Loop Design Algorithms can be used.
IIR Filter Disadvantages
Non Linear Phase response Limit cycle may occur for integer
implementation Multiband design is difficult Feedback can introduce instabilities Difficult to get high Speed, pipelines design
Summary of Important IIR Design
Butterworth: Maximally –flat passband, flat stopband, wide
transitionband : Filter order highest Chebyshev-I
Equiripple passband, flat stopband, moderate transition band
Chebyshev II Flat passband, equiripple stopband, moderate
transition band : Filter Order Medium Elliptic:
Equiripple passband, equiripple stop band narrow transition bnad : Filter order : Lowest