SIGNAL PROCESSING

1. ADAPTIVE FILTERS
PRESENTED BY:
PRANOTI BACHHAV

2. ADAPTIVE FILTERS:
 The adaptive filter is able to operate in an unknown environment and to
track variations of the input signals.
 The MATLAB Filter Design Toolbox provides the function adapfilt for
implementing adaptive filters. The function
 H= adapfilt.algorithm(…);

3. ADPATIVE FILTER SYSTEM
IDENTIIFCATION
 D(n)
P(Z)
W(Z)
LMS
X(n)
E(n)
Y(n )

4.  P(Z) is an unknown system to be identified.
 W(Z) is an adaptive filter.
 X(n) provides sufficient excitation.
 The filter output will approximate d(n) in an optimum sense after
convergence.
 When the difference between the physical system response d(n) and the
adaptive model response y(n) has been minimized.

5. ADPATIVE FILTER SYSTEM PREDICTION
W(Z)
LMS
X(n)
E(n)
Y(n )
Y(n)
Z
D(n)

6.  The adaptive prediction provides efficient tracking of the sinusoidal
components of d(n) and separated narrowband signal from broadband
noise.
 Delay should be 1 to correlate white noise component between d(n) an
x(n).

7. W(Z)
LMS
E(n)
Y(n )
Y(n)
Z
Primary sensor
NOISE CANCELLATION
Ref
sensor
D(n)

8. ADPATIVE FILTER CHANNEL EQUALIZER
 D(n)
W(Z)
LMS
X(n)
E(n)
Y(n )
C(Z)