# DSP Interview Preparation Guide **Download PDF** Add New Question

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DSP frequently Asked Questions in various DSP job Interviews by interviewer. Get preparation of DSP job interview

## 9 DSP Questions and Answers:

### 1 :: Please write a code in C / Verilog to implement a basic FIR filter?

%program for FIR filters

disp('choose the window from the list');

ch=menu('types of

windows','bartlett','blackman','hamming','hanning','kaiser',

'rectangular');

rp=input('enter the passband ripple in db');

rs=input('enter the stopband ripple in db');

wsample=input('enter sampling frequency in hertz');

wp=input('enter the passband frequency in hertz');

ws=input('enter the stopband frequency in hertz');

wp=2*wp/wsample; ws=2*ws/wsample;

p=20*log10(sqrt(rp*rs))-13;

q=14.6*(ws-wp)/wsample;

N=1+floor(p/q);

N1=N;

if(rem(N,2)==0)

N1=N+1;

else

N=N-1;

end

switch ch

case 1

y=bartlett(N1);

case 2

y=blackman(N1);

case 3

y=hamming(N1);

case 4

y=hanning(N1);

case 5

beta=input('enter beta for kaiser window');

y=kaiser(N1,beta);

case 6

y=boxcar(N1);

otherwise

disp('enter proper window number');

end

disp('select the type of filter from the list');

type=menu('types of

filters','lowpass','highpass','bandpass','bandstop');

switch type

case 1

b=fir1(N,wp,'low',y);

case 2

b=fir1(N,wp,'high',y);

case 3

b=fir1(N,[wp ws],'bandpass',y);

case 4

b=fir1(N,[wp ws],'stop',y);

otherwise

disp('enter type number properly');

end

[h,w]=freqz(b,1,512);

magn=20*log10(abs(h));

phase=(180/pi)*unwrap(angle(h));

w=(w*wsample)/(2*pi);

subplot(2,1,1); plot(w,magn),grid on;title('magnitude

plot'); subplot(2,1,2); plot(w,phase),grid on;title('phase

plot');

disp('choose the window from the list');

ch=menu('types of

windows','bartlett','blackman','hamming','hanning','kaiser',

'rectangular');

rp=input('enter the passband ripple in db');

rs=input('enter the stopband ripple in db');

wsample=input('enter sampling frequency in hertz');

wp=input('enter the passband frequency in hertz');

ws=input('enter the stopband frequency in hertz');

wp=2*wp/wsample; ws=2*ws/wsample;

p=20*log10(sqrt(rp*rs))-13;

q=14.6*(ws-wp)/wsample;

N=1+floor(p/q);

N1=N;

if(rem(N,2)==0)

N1=N+1;

else

N=N-1;

end

switch ch

case 1

y=bartlett(N1);

case 2

y=blackman(N1);

case 3

y=hamming(N1);

case 4

y=hanning(N1);

case 5

beta=input('enter beta for kaiser window');

y=kaiser(N1,beta);

case 6

y=boxcar(N1);

otherwise

disp('enter proper window number');

end

disp('select the type of filter from the list');

type=menu('types of

filters','lowpass','highpass','bandpass','bandstop');

switch type

case 1

b=fir1(N,wp,'low',y);

case 2

b=fir1(N,wp,'high',y);

case 3

b=fir1(N,[wp ws],'bandpass',y);

case 4

b=fir1(N,[wp ws],'stop',y);

otherwise

disp('enter type number properly');

end

[h,w]=freqz(b,1,512);

magn=20*log10(abs(h));

phase=(180/pi)*unwrap(angle(h));

w=(w*wsample)/(2*pi);

subplot(2,1,1); plot(w,magn),grid on;title('magnitude

plot'); subplot(2,1,2); plot(w,phase),grid on;title('phase

plot');

### 2 :: Do you know How is the non-periodic nature of the input signal handled?

Fourier series is applied for periodic signals since they

violate Dirchilet's conditions. This will give the

fundamental and harmonic signal components for periodic

signals.

For non-periodic signals if we need frequency analysis as a

whole then fourier transform is applied for the entire

duration. Provided its energy is finite and follows other

conditions as laid out by Dirchilet.

violate Dirchilet's conditions. This will give the

fundamental and harmonic signal components for periodic

signals.

For non-periodic signals if we need frequency analysis as a

whole then fourier transform is applied for the entire

duration. Provided its energy is finite and follows other

conditions as laid out by Dirchilet.

### 3 :: What is the difference between ProtoPlus and ProtoPlus Lite?

ProtoPlus prototyping daughter card - A plug-in,

2-connector, multi-layer, low noise, and stackable

prototyping board that plugs into the Texas Instruments DSK

and EVM DSP development systems.

ProtoPlus Lite prototyping daughter card - A Low cost,

2-connector, plug-in prototyping board that plugs into the

Texas Instruments DSK and EVM DSP development systems.

2-connector, multi-layer, low noise, and stackable

prototyping board that plugs into the Texas Instruments DSK

and EVM DSP development systems.

ProtoPlus Lite prototyping daughter card - A Low cost,

2-connector, plug-in prototyping board that plugs into the

Texas Instruments DSK and EVM DSP development systems.

### 4 :: Can we create a table with out primary key?

yes we can create

CREATE TABLE Orders

(

OrderID SMALLINT UNSIGNED NOT NULL PRIMARY KEY,

ModelID SMALLINT UNSIGNED NOT NULL,

ModelDescrip

);

CREATE TABLE Orders

(

OrderID SMALLINT UNSIGNED NOT NULL PRIMARY KEY,

ModelID SMALLINT UNSIGNED NOT NULL,

ModelDescrip

);

### 5 :: Explain what is dirac delta function and its fourier transform and its importance?

Dirac delta is a continuous time function with unit area and

infinite amplitude at t=0.

the fourier transform of dirac delta is 1.

using dirac delta as an input to the system, we can get the

system respnose. it is used to study the behavior of the

circuit.

we can use this system behavior to find the output for any

input.

infinite amplitude at t=0.

the fourier transform of dirac delta is 1.

using dirac delta as an input to the system, we can get the

system respnose. it is used to study the behavior of the

circuit.

we can use this system behavior to find the output for any

input.

### 6 :: Suppose we are sending address of thesalve and then data then after i want to read the data which i was sent recently, in that case before im reading is there any need to send a stop bit before read?

Before reading the data if you are giving the stop bit then

the communication is stopped.so after sending the data you

will give the stop bit.

the communication is stopped.so after sending the data you

will give the stop bit.

### 7 :: How do we implement a fourth order Butterworth LP filter at 1kHz if sampling frequency is 8 kHz?

A fourth order Butterworth filter can be made as cascade of

two seond order LP filters with zeta of 0.924 and 0.383.

One can use a bilinear transformation approach for

realising second order LP filters. Using this technique

described well in many texts, one can make two second order

LP filters and cascade them.

two seond order LP filters with zeta of 0.924 and 0.383.

One can use a bilinear transformation approach for

realising second order LP filters. Using this technique

described well in many texts, one can make two second order

LP filters and cascade them.

### 8 :: What is an anti aliasing filter and why is it required?

Anti aliasing filter reduces errors due to aliasing. If a

signal is sampled at 8 kS/S, the max frequency of the input

should be 4 kHz. Otherwise, aliasing errors will result.

Typically a 3.4kHz will have an image of 4.6 khz, and one

uses a sharp cut off filter with gain of about 1 at 3.4kHz

and gain of about 0.01 at 4.6 kHz to effectively guard

against aliasing. Thus one does not quite choose max

frequency as simply fs/2 where fs is sampling frequency.

One has to have a guard band of about 10% of this fmax, and

chooses max signal frequency as 0.9*fs/2

signal is sampled at 8 kS/S, the max frequency of the input

should be 4 kHz. Otherwise, aliasing errors will result.

Typically a 3.4kHz will have an image of 4.6 khz, and one

uses a sharp cut off filter with gain of about 1 at 3.4kHz

and gain of about 0.01 at 4.6 kHz to effectively guard

against aliasing. Thus one does not quite choose max

frequency as simply fs/2 where fs is sampling frequency.

One has to have a guard band of about 10% of this fmax, and

chooses max signal frequency as 0.9*fs/2

### 9 :: Explain Is the Gibbs phenomenon ever a factor?

Yes Gibbs phenomenon becomes constraining when we are

analysing signals containing frequency tones quite close to

each other. If the side lobes of the windowing function are

significant then it leads to energy leakages between the

frequency bins/sub-bands. Thus very close lying frenecy

tones gets their magnitudes smeared up in the process.

analysing signals containing frequency tones quite close to

each other. If the side lobes of the windowing function are

significant then it leads to energy leakages between the

frequency bins/sub-bands. Thus very close lying frenecy

tones gets their magnitudes smeared up in the process.