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Part I (Filter design and signal analysis) Problem 1 A filter is given by the input-output difference equation y[n]=1/21 (-2x[n]+3x[n-1]+6x[n-2]+7x[n-3]+6x[n-4]+3x[n-5]-2x[n-6])

1) An electrocardiogram (ECG) signal is corrupted by muscle noise. Explain why processing the signal with this filter would be useful.

2) Design and implement a recursive filter that would be suitable for the ECG signal of part 1).

3) Find a simple expression for the output of each of these two filters if the input is the signal x[n]=cos(0.35n). Problem 2 The spectrogram of a signal can be computed using the Matlab function Spectrogram (specgram in older versions of Matlab).

1) Using appropriate references, explain what the spectrogram of a signal is (maximum 1000 words).

2) Use the Matlab function Spectrogram to analyse the audio signal “MainStreetOne-24-96-stereo-63secs.wav”. Part II (Video processing) Read Section II-D of the article T. K. Tan et al., "Video Quality Evaluation Methodology and Verification Testing of HEVC Compression Performance," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 1, pp. 76-90, Jan. 2016.

1) What is the benefit of computing the Bjøntegaard-Delta (BD) metric instead of only comparing the operational rate-distortion curves of the two codecs? Read appropriate references on the BD metric to help you answer this question.

2) For each video quality metric (MOS and PSNR), find the values of DH and DL corresponding to Figure 5 in the above cited paper.

3) With reference to Figure 5, use the Matlab code provided here http://uk.mathworks.com/matlabcentral/fileexchange/27798-bjontegaard-metric?focused=5154715&tab=function to calculate the BD-rate for the two video quality metrics.

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Title Abstract I Introduction  II System Model: the equations, the simulink model figure and system hardware figure are essential.  Ill Controller Design: 1) Linearisation 2) State feedback design 3) zero-pole map as a figure  IV Simulation with discussion: 1) Model simulation (1 s ...

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