DSP System Toolbox blocks in Simulink - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a lowpass FIR filter block using DSP System Toolbox.

Simulink

lpFilt = dsp.FIRFilter('Numerator', [1]);

Drag options to blanks, or click blank then click option'

A[0 1 0 1 0]

B[0.2 0.2 0.2 0.2 0.2]

C[1 2 3 2 1]

D[1 0 0 0 1]

Attempts:

3 left

💡 Hint

Common Mistakes

Using coefficients that do not sum to 1.

Using coefficients that create a highpass filter instead.

The 'Numerator' property defines the filter coefficients. A simple lowpass FIR filter can be created with equal coefficients summing to 1, like [0.2 0.2 0.2 0.2 0.2].

2fill in blank

medium

Complete the code to create a spectrum analyzer block with a sample rate of 1000 Hz.

Simulink

specAnalyzer = dsp.SpectrumAnalyzer('SampleRate', [1]);

Drag options to blanks, or click blank then click option'

A1000

B500

C2000

D50

Attempts:

3 left

💡 Hint

Common Mistakes

Using a sample rate different from the signal's actual rate.

Confusing sample rate with frequency resolution.

The 'SampleRate' property sets the sample rate for the spectrum analyzer. Here, 1000 Hz is the correct value.

3fill in blank

hard

Fix the error in the code to create a decimator block with a decimation factor of 4.

Simulink

decim = dsp.Decimator('DecimationFactor', [1]);

Drag options to blanks, or click blank then click option'

A4

B3

C2

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using a decimation factor that does not match the desired downsampling.

Using a non-integer decimation factor.

The 'DecimationFactor' must be set to 4 to correctly decimate the signal by a factor of 4.

4fill in blank

hard

Fill both blanks to create a bandpass filter with lower cutoff 100 Hz and upper cutoff 300 Hz.

Simulink

bpFilt = dsp.BandpassFilter('LowerCutoffFrequency', [1], 'UpperCutoffFrequency', [2]);

Drag options to blanks, or click blank then click option'

A100

B200

C300

D400

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping lower and upper cutoff frequencies.

Using frequencies outside the signal bandwidth.

The bandpass filter requires the lower cutoff frequency to be 100 Hz and the upper cutoff frequency to be 300 Hz.

5fill in blank

hard

Fill all three blanks to create a variable bandwidth filter with center frequency 500 Hz, bandwidth 200 Hz, and sample rate 2000 Hz.

Simulink

varFilt = dsp.VariableBandwidthFilter('CenterFrequency', [1], 'Bandwidth', [2], 'SampleRate', [3]);

Drag options to blanks, or click blank then click option'

A400

B500

C2000

D200

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up bandwidth and center frequency values.

Using incorrect sample rate.

The center frequency is 500 Hz, bandwidth is 200 Hz, and sample rate is 2000 Hz as specified.

Practice

1. Which of the following is a primary use of DSP System Toolbox blocks in Simulink?

easy

A. To manage database connections

B. To write low-level hardware drivers

C. To create 3D animations

D. To build and simulate signal processing systems visually

Solution

1. Step 1: Understand the purpose of DSP System Toolbox blocks

   These blocks are designed to help build and simulate signal processing systems visually in Simulink.

2. Step 2: Eliminate unrelated options

   The remaining options relate to hardware drivers, animations, and databases, which are not functions of DSP System Toolbox blocks.

3. Final Answer:

   To build and simulate signal processing systems visually -> Option D

4. Quick Check:

   DSP System Toolbox = Visual signal processing [OK]

Hint: Remember DSP blocks are for signal processing, not hardware or graphics [OK]

Common Mistakes:

• Confusing DSP blocks with hardware programming
• Thinking DSP blocks create animations
• Assuming DSP blocks manage databases

2. Which block from the DSP System Toolbox is used to perform a Fast Fourier Transform (FFT) in Simulink?

easy

A. FFT block

B. Gain block

C. Scope block

D. Filter block

Solution

1. Step 1: Identify the block for frequency analysis

   The FFT block is specifically designed to compute the Fast Fourier Transform of signals.

2. Step 2: Confirm other blocks' functions

   Filter blocks modify signals, Scope blocks display signals, and Gain blocks multiply signals by a constant.

3. Final Answer:

   FFT block -> Option A

4. Quick Check:

   FFT block = Fast Fourier Transform [OK]

Hint: FFT block always computes frequency transform [OK]

Common Mistakes:

• Choosing Filter block for FFT
• Confusing Scope block with processing block
• Selecting Gain block for transform

3. Given a Simulink model using a DSP System Toolbox FIR Filter block with coefficients [1 2 1], what is the output for input signal [1 0 0 0]?

medium

A. [1 0 0 0]

B. [1 2 1 0]

C. [0 1 2 1]

D. [1 3 3 1]

Solution

1. Step 1: Understand FIR filter output calculation

   The output is the convolution of input signal with filter coefficients [1 2 1].

2. Step 2: Compute convolution of [1 0 0 0] and [1 2 1]

   Convolution result is [1*1, 1*2+0, 1*1+0, 0] = [1, 2, 1, 0].

3. Final Answer:

   [1 2 1 0] -> Option B

4. Quick Check:

   Input convolved with coefficients = output [OK]

Hint: FIR output = input convolved with coefficients [OK]

Common Mistakes:

• Ignoring convolution and taking input as output
• Reversing coefficient order incorrectly
• Adding coefficients instead of convolving

4. You have a Simulink model using a DSP System Toolbox block that throws an error: "Input signal dimension mismatch." What is the most likely cause?

medium

A. The input signal size does not match the block's expected input dimension

B. The block is missing from the library

C. The output signal is connected incorrectly

D. The Simulink version is outdated

Solution

1. Step 1: Analyze the error message

   The error "Input signal dimension mismatch" indicates the input size is not what the block expects.

2. Step 2: Check common causes

   Missing blocks or output connection errors cause different errors; version issues rarely cause dimension mismatch.

3. Final Answer:

   The input signal size does not match the block's expected input dimension -> Option A

4. Quick Check:

   Dimension mismatch = input size error [OK]

Hint: Dimension mismatch means input size is wrong [OK]

Common Mistakes:

• Assuming missing block causes dimension error
• Blaming output connection for input dimension error
• Ignoring input size requirements

5. You want to design a Simulink model using DSP System Toolbox blocks to filter noise from a signal sampled at 1 kHz. Which combination of blocks is best suited for this task?

hard

A. FFT block and Constant block

B. Gain block and Scope block

C. FIR Filter block with lowpass coefficients and Spectrum Analyzer block

D. Mux block and Demux block

Solution

1. Step 1: Identify blocks for noise filtering

   The FIR Filter block can remove unwanted frequencies using lowpass coefficients.

2. Step 2: Identify blocks for signal analysis

   The Spectrum Analyzer block helps visualize the frequency content to verify filtering.

3. Step 3: Evaluate other options

   Gain and Scope do not filter noise; FFT and Constant do not filter; Mux/Demux combine signals but do not filter.

4. Final Answer:

   FIR Filter block with lowpass coefficients and Spectrum Analyzer block -> Option C

5. Quick Check:

   Filter + Analyzer = noise removal and check [OK]

Hint: Use filter block to remove noise, analyzer to check [OK]

Common Mistakes:

• Choosing Gain or Scope for filtering
• Using FFT without filtering
• Confusing signal combining blocks with filtering