Antinoise system & Noise Cancellation

Anti Noise System&

Noise Cancellation

By :- Bhargav Khambhata

(Electrical Department)

ContentsContents

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.

What is noiseWhat is noise??

Fiq (1):AWGN

Noise consists of unwanted waveforms that can interfere with communication.

Sound noise: interferes with your normal hearing

• Loud noises

• Subtle noise

• White noise (AWGN)

Active and passive noiseActive and passive noiseThe 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

What is Noise CancellationWhat is Noise Cancellation??

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

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.

Simple IdeaSimple IdeaCancellation processes depend on simple principle adding two signals with the same . amplitude and opposite phase the result will be zero signals.

(H)

Types of wave cancellation

wave cancellation

Simple wave complex wave

Simple wave cancellationSimple wave cancellation

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

Canceling complex wavesCanceling complex waves

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.

Active Noise Cancellation Active Noise Cancellation (ANC)(ANC)

Design ConsiderationsActive 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. 

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.

ApplicationsApplications

Headsets (headphone) Honda cars. Space satellite antennas. Use in apartment. NoiseMuter

NoiseMuter)NoiseMuter) Noise Noise CancellerCanceller))

Condition/coderOriginalNoiseMuter Processed

Speech + Car Noise

Original NoiseMuter processed

NoiseMuter is an advanced noise suppression solution, designed as add-on software module to enable noise-free communication.

Adaptive filterAdaptive filter

• nonlinear and time-variant .

• adjust themselves to an ever-changing environment .

• changes its parameters so its performance improves through its surroundings.

Adaptive FilterAdaptive Filter

The coefficients of an adaptive filter change in time

Output signal

Input signal

Adaptive algorithm

Criterion of performance

Filter structure

Comparison Comparison (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

Block diagram of adaptive systemBlock diagram of adaptive system

S)n(+No)n(No)n(

+

-

?

Primary signal

d)n(

N1)n(

Reference signal

y)n(output

e)n(

adaptive

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.

LMS algorithmLMS algorithm

Estimates the solution to the Weiner-Hopf equations using gradient descent method which finds minima by estimating the gradient.

• is the step size

e

X)n(

C)n(

Transversal Filter

LMS

Y)n(

e)n(

d)n(

Update the coefficients using the following computation.

filtering operation with the previous version of the coefficients.

Compare the computed output with the expected output.

e)n(

X)n( y)n(

d)n(

Adaptive filter

Unknown system

ExperimentExperimentClick to listen original sound

Click to listen nosily sound

Click to listen output1 sound

Click to listen output 2 sound

conclusionconclusion

• 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 .

Thank You