My first question is: Design a digital filter with the following specifications:

Question

My first question is:

Design a digital filter with the following specifications:
Cutoff frequency = 800 Hz
Sampling rate = 10,000
Low-pass filter
What is the digital normalized frequency in radians?style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">

1)0.16 pie

2)0.8 pie

3)3.2 pie

4)pie/16

Explain?

My second question is :

A DSP engineer used the following MATLAB code to perform offline digital filtering
>> y=filter([1, 0.8, 0.8],[1],x);
Where x and y are the input and output vectors, respectively. Which of the following is the transfer function?style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">

1)H(z)=0.4-.07z^-1+0.85z^-2

2)H(z)=0.5-z^-1+0.5z^-2

3)H(z)=0.8+0.8z^-1

4)H(z)=1+0.8z^-1+0.8z^-2

Explain?

My  third question is:

We want to design  a 7-tap band-pass FIR filter with linear phase response. The lower  cutoff frequency is 1,200 Hz, and upper cutoff frequency is 2400 Hz. The  sampling frequency is 8,000 Hz. Which of the following is the filter  impulse response?style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">

1)-0.0951, -0.245, -0.0452, 0.3, 0.0452, -0.245, -0.0951style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">for="multiplechoice7_0_1">

2)-0.0951, -0.245, 0.0452, 0.3, 0.0452, -0.245, -0.0951style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">for="multiplechoice7_0_2">

3)-0.951, -0.245, 0.0452, 0.6, 0.0452, -0.245, -0.951style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">for="multiplechoice7_0_3">style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">for="multiplechoice7_0_2">

4) -0.0951, -0.245, 0.0452, 0.0452, -0.245, -0.0951style="font-family: 'verdana'; font-size: 10pt;" data-mce-style="font-family: 'verdana'; font-size: 10pt;">for="multiplechoice7_0_4">

explain?

My Fith question is:

A DSP engineer used the following MATLAB code to perform offline digital filtering
>> y=filter([0.8, 0.8],[1],x);
Where x and y are the input and output vectors, respectively. Which of the following is the difference equation?style="font-family: 'verdana'; font-size: 10pt;">

1) y(n)=0.8x(n)+0.8x(n-1)style="font-family: 'verdana'; font-size: 10pt;">

2) y(n)=x(n)+0.8x(n-1)+0.8x(n-2)style="font-family: 'verdana'; font-size: 10pt;">

3) y(n)=x(n)-0.5x(n-1)+x(n-2)style="font-family: 'verdana'; font-size: 10pt;">

4) y(n)=0.25x(n)-0.75x(n-1)+0.25x(n-2)
>

PLEASE TRY TO ANSWER IN THE NEXT 20 MIN!!!
>

Explanation / Answer

Infinite impulse response

Infinite impulse response (IIR) is a property applying to many linear time-invariant systems. Common examples of linear time-invariant systems are most electronic and digital filters. Systems with this property are known as IIR systems or IIR filters, and are distinguished by having an impulse response which does not become exactly zero past a certain point, but continues indefinitely. This is in contrast to a finite impulse response in which the impulse response h(t) does become exactly zero at times t > T for some finite T, thus being of finite duration.

In practice, the impulse response even of IIR systems usually approaches zero and can be neglected past a certain point. However the physical systems which give rise to IIR or FIR responses are dissimilar, and therein lies the importance of the distinction. For instance, analog electronic filters composed of resistors, capacitors, and/or inductors (and perhaps linear amplifiers) are generally IIR filters. On the other hand, discrete-time filters (usually digital filters) based on a tapped delay line employing no feedback are necessarily FIR filters. The capacitors (or inductors) in the analog filter have a "memory" and their internal state never completely relaxes following an impulse. But in the latter case, after an impulse has reached the end of the tapped delay line, the system has no further memory of that impulse and has returned to its initial state; its impulse response beyond that point is exactly zero.

Implementation and design[edit source | editbeta]

Although almost all analog electronic filters are IIR, digital filters may be either IIR or FIR. The presence of feedback in the topology of a discrete-time filter (such as the block diagram shown below) generally creates an IIR response. The z domain transfer function of an IIR filter contains a non-trivial denominator, describing those feedback terms. The transfer function of an FIR filter, on the other hand, has only a numerator as expressed in the general form derived below. All of the a_i coefficients (feedback terms) are zero and the filter has no finite poles.

The transfer functions pertaining to IIR analog electronic filters have been extensively studied and optimized for their amplitude and phase characteristics. These continuous-time filter functions are described in the Laplace domain. Desired solutions can be transferred to the case of discrete-time filters whose transfer functions are expressed in the z domain, through the use of certain mathematical techniques such as the bilinear transform, impulse invariance, or pole

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