Antinoise system and noise cancellation ppt.........

1. Anti Noise System
&
Noise Cancellation
By :- Bhargav Khambhata
(( Electrical Department

2. CCoonntteennttss 
 What is noise?
 What is noise cancellation?
 Simple idea.
 Wave cancellation.
 Active noise cancellation (ANC(.
 Applications.
 Adaptive filter.
 Comparison
 Adaptive algorithm (LMS & RMS(.
 Simulation.
 Conclusion.

3. ??WWhhaatt iiss nnooiissee
 Noise consists of unwanted
waveforms that can interfere with
communication.
 Sound noise: interferes with your
normal hearing
• Loud noises
• Subtle noise
• White noise (AWGN(
Fiq (1(:AWGN

4.  AAccttiivvee aanndd ppaassssiivvee nnooiissee
The advantages of active noise control
methods compared to passive ones are
that they are generally:
• More effective at low frequencies.
• Less bulky.
• Able to block noise selectively

5. ??WWhhaatt iiss NNooiissee CCaanncceellllaattiioonn
 Noise cancellation is a method to reduce or
completely cancel out undesirable sound
 call as Active Noise Cancellation .
 Noise cancellation tries to 'block' the sound at
the source instead of trying to prevent the
sounds from entering our ear canals

6.  These technologies are in their early
stages.
 The hope is that one day that these
technologies can be used to minimize all
sorts of unwanted sounds around us.

7. SSiimmppllee IIddeeaa
Cancellation processes depend on simple
principle
 adding two signals with the same .
 amplitude and opposite phase the result
will be zero signals.
(H)

8.  Types of wave cancellation
wave cancellation
Simple wave complex wave

9.  SSiimmppllee wwaavvee ccaanncceellllaattiioonn
Simple sine wave for single
sound frequency
One pure sound a fraction of
a second after the next
Sum of two waves
slightly out of phase
Sum of two waves slightly
out of phase

10. CCaanncceelliinngg ccoommpplleexx wwaavveess
 A spoken word consists of
a spectrum of frequencies of
different amplitude
 need to filter each
frequency separately,
 create the same frequency
and amplitude at 180° out of
phase.

11. ((Active NNooiissee CCaanncceellllaattiioonn ((AANNCC

12. Design Considerations
Active Noise Cancellation (ANC)
 The active noise cancellation system implements the
acoustically adaptive algorithm that cancels the unwanted
sound by generating an antisound (antinoise( of equal amplitude
and opposite phase. The original, unwanted sound and the
antinoise acoustically combine, resulting in the cancellation of
both sounds.
 The core subsystems include:
• DSP
performs system initialization and executes the adaptive
signal processing algorithm.

13.  Memory
- stores executing code and data/parameters.
 AGC
- maximizes the ADC SNR and maintains the overall system dynamic
range.
 Audio CODEC
- the residual noise signals are converted o digital form by the ADC.
- The DAC generates the out put anti-noise signals.
 Power Conversion
- converts the battery power to run various functional blocks.

14. AApppplliiccaattiioonnss
 Headsets (headphone(
 Honda cars.
 Space satellite antennas.
 Use in apartment.
 NoiseMuter

16. ))NNooiisseeMMuutteerr)) NNooiissee CCaanncceelllleerr
 NoiseMuter is an advanced noise suppression
solution, designed as add-on software module to
enable noise-free communication.
Condition/coder Original NoiseMuter Processed
Speech + Car
Noise
Original NoiseMuter
processed

17.  AAddaappttiivvee ffiilltteerr
• nonlinear and time-variant .
• adjust themselves to an ever-changing
environment .
• changes its parameters so its
performance improves through its
surroundings.

18. AAddaappttiivvee FFiilltteerr
Output
signal
Input
signal
Filter
structure
Adaptive
algorithm
Criterion of
performance
The coefficients of an adaptive filter change
in time

19. CCoommppaarriissoonn
((supervised vs. unsupervised
 Expected output is known.
quantity .
 The Criterion of
Performance can simply
take the difference
between actual output and
desired.
 It uses information to tell
the Adaptation Algorithm
what adjustments to make.
 Expected output is
unknown quantity.
 the Criterion of
Performance has to do.
We cannot simply take
 the difference actual and
desired output consists of
looking for signal qualities

20. Block ddiiaaggrraamm ooff aaddaappttiivvee ssyysstteemm
)S(n)+No(n
)No(n
+
-
?
Primary
signal
)d(n
)N1(n
Reference
signal
)y(n output
)e(n
adaptive

21. Adaptive algorithm
 An adaptive algorithm is used to estimate a time
varying signal.
 By adjusting the filter coefficients so as to
minimize the error.
 There are many adaptive algorithms like
Recursive
 Least Square )RLS(, Kalman filter,
 but the most commonly used is the Least Mean
Square )LMS( algorithm.

22. LLMMSS aallggoorriitthhmm
 Estimates the
solution to the
Weiner-Hopf
equations using
gradient descent
method which finds
minima by
estimating the
gradient.
• is the step size
(d(n
e
(X(n
Transversal
Filter
(C(n
LMS
(Y(n
(e(n

23.  filtering operation with the
previous version of the coefficients.
 Compare the computed output
with the expected output.
Update the coefficients using
the following computation.
(e(n
(X(n (y(n
(d(n
Adaptive
filter
Unknown
system

24. EExxppeerriimmeenntt
Click to listen original
sound
Click to listen nosily
sound
Click to listen output1
sound
Click to listen output 2
sound

25. ccoonncclluussiioonn
• Active noise cancellation is a method to cancel
out undesirable sound in real time.
• The adaptive filter is used to estimate the error
in noisy wave
• Many algorithms are used in adaptive filter like
LMS RLS & MSE and the better is RLS .

26. Thank You