Filters are normally specified in terms of a power response.Filters are normally specified in terms of a power response.fcis defined as the point where the power output is 1/2 the inputpowerThis power ratio is given in decibels by P(db) = 10log10(0.5) = −3dbHowever MATLAB designs filters according to the voltage ratioYou may remember P = V 2R. Thus the voltage ratio isV (db) = 20log10(0.5) = −6dbTherefore the filter you design should have a -6db output at thefrequencies assigned to youOptimising filters, part AFIR Digital filters are formed from delays, multipliers and sums, e.g.The ORDER of the filter is the number of delay blocks in it. Thehigher the order, the more ideal a filter response you can create.However the phase delay is greater, and circuit more complex.For this coursework you’ve been assigned a specific order to use.Therefore some of your filters will have a better response than othersThe remaining parameters of the design determine how thecoefficients of multiplication are chosen, different filter types usedifferent co-efficient schemes, which in turn have different filterresponses.Optimising filters, part A cont…You should experiment with the sampling frequency, the differentfilter types, and different settings for them, in order to make yourfilter as close to ’ideal’ as possible.Then in your report, explain why you chose these settings andcompare the performance to another filter designThe output of this stage of the coursework is a set of coefficients thatdescribe the filter. The number of coefficients should equal the orderof your filter.Part BExplore the ’filter’ command, work out how to use it to filter datausing the filter coefficients derived in Part A.A ’m-file’ is just a file that contains a ’m-command’, as introduced inthe introduction to MATLAB tutorial Coventry University Faculty of Engineering and ComputingCoursework Task Sheet – be sure to keep a copy of all work submitted Section A – To be completed by the studentFamily Name(s) ModuleNo.310SEForename(s) ID Number(s) (from your student card) Submit via the module Moodle site by 23:55 on27th June 2016 Time taken (hrs) (per student for group coursework)  LecturerDr Andrew Jason Tickle Hand out date:25th April 2016 Module Code and Title310SE – Advanced Digital Systems No late work accepted. Extensions allowed only in extenuating circumstances. It is importantthat the work submitted is an individual effort. The penalties for plagiarism are severe.Full details on Faculty coursework policy and procedures are available athttps://students.coventry.ac.uk/EC/Pages/Procedures.aspx Assignment No. / TitlePractical Coursework Estimated Time (hrs)20 Assignment type:Individual % of Module Mark30%Section B – To be completed by the assessorMarks breakdown Max Awarded
1. Create a filter using your unique specification using the FDA tool in Matlab and draw the filter configuration. 2. Implement the system in Matlab or Simulink and then input various frequencies into the system to test if the filter works correctly so that you produce an amplitude vs frequency characteristic graph. 3. Contaminate the input signal frequency with noise and develop an effective noise-removal methodology, discussing the effects on the filter compared to the signal without noise.Increase the noise density and investigate the limit to which the noise can be removed before the loss of data is irreversible. 4. Write your results into a professional report with correct layout, formatting and English. 20
35

35

10 Assessor’s signature Total100 TotalInternal moderators’ signature
This section may be used for feedback or other information

Learning outcomes assessed:1. Employ appropriate computing languages for the simulation of digital signal processing functions.2. Produce theoretical models of DSP applications and solutions, for example, noise removal filters and signal processing techniques.
Assessment criteria
Class Mark range Guidelines
First Class 70 – 79%

80 – 89%

90 – 100% Answer entirely relevant to the assignment set.  Answer will demonstrate clear understanding of theories, concepts, issues and methodology, as appropriate.  There will be evidence of wide-ranging reading and/or research, as appropriate, beyond the minimum recommended. Answers will be written / presented in a clear, well-structured way with clarity of expression.  Evidence of independent, critical thought would normally be expected.
In addition to the above, the answer will demonstrate an excellent level of understanding, presence of clear description, critical/analytical skills or research, as appropriate.
In addition to the above, an outstanding answer that could hardly be bettered.  High degree of understanding, critical/analytic skills and original research, where specified.  Outstanding in all respects.
Upper Second Class 65 – 69%

60 – 64% Answer demonstrating a very good understanding of the requirements of the assignment.  Answer will demonstrate very good understanding of theories, concepts, issues and methodology, as appropriate.  Answer will be mostly accurate/appropriate, with few errors.  Little, if any, irrelevant material may be present.    Reading beyond the recommended minimum will be present where appropriate.  Well organised and clearly written/presented.
A good understanding, with few errors.  Some irrelevant material may be present.  Well organised and clearly written/presented.  Some reading/research beyond recommended in evidence.
Lower Second Class 55 – 59%

50 – 54% Answer demonstrating a good understanding of relevant theories, concepts, issues and methodology.  Some reading/research beyond that recommended may be present.  Some errors may be present and inclusion of irrelevant material.  May not be particularly well-structured, and/or clearly presented.
Answer demonstrating a reasonable understanding of theories, concepts, issues and methodology.  Answer likely to show some errors of understanding.  May be significant amount of irrelevant material.  May not be well-structured and expression/presentation may be unclear at times.
Pass 45 – 49%

READ ALSO :   Pain Management and Nursing Practice

40 – 44% An understanding demonstrated, but may be incomplete and with some errors.  Limited use of material with limited reading/research on the topic.  Likely to be poorly structured and not well-expressed/presented.  Irrelevant material likely to be present.
Basic understanding demonstrated, with some correct description. Answer likely to be incomplete with substantial errors or misunderstandings.  Little use of material and limited reading/research on the topic in evidence.  May be poorly structured and poorly expressed/presented.  Some material may be irrelevant to the assignment requirements.
A mark of 40% indicates that the student’s work just achieves the Intended Learning Outcomes (ILO) of the assessment task.

Marginal fail 35 – 39% Some relevant material will be present. Understanding will be poor with little evidence of reading/research on the topic.  Fundamental errors and misunderstanding likely to be present.  Poor structure and poor expression/presentation.  Much material may not be relevant to the assignment.
Fail 30 – 34%

20 – 29%

0 – 19% Inadequate answer with little relevant material and poor understanding of theories, concepts, issues and methodology, as appropriate.  Fundamental errors and misunderstandings will be present.  Material may be largely irrelevant.  Poorly structured and poorly expressed/presented.
Clear failure to provide answer to the assignment.  Little understanding and only a vague knowledge of the area.  Serious and fundamental errors and lack of understanding.  Virtually no evidence of relevant reading/research.  Poorly structured and inadequately expressed/presented.
Complete failure, virtually no understanding of requirements of the assignment.  Material may be entirely irrelevant.  Answer may be extremely short, and in note form only.  Answer may be fundamentally wrong, or trivial.  Not a serious attempt.

Your mark will consist of the following components
Part Assignment Details Marks

A This will involve the design of thefilter in Matlab using the Filter Design and Analysis (FDA) Toolbox. You will create an IIR filter using your own parameters to make your filter design unique, can choose the type of IIR filter and window. The cut-off frequency will be in kHz and will be designed from the first two digits of your unique student identification number. If you have a band-pass or band stop configuration, please use the first two digits as one cut off frequency and the third and fourth and the second cut off frequency. In the event that the first number is higher than the second, swap the numbers around. After you have found the coefficient’s for your system, please draw the configuration for your filter.

20%

B Implement your system in Matlab by creating an m-file for the configuration that you drew in part A. After you have programmed your system, you will then need to test it by inputting signals and varying frequencies then plotting the output of the filter to see if the input has been attenuated or not. Once the filter is working correctly, you will then need to create an amplitude vs frequency plot that is suitable for your unique cut-off frequency. Compare this against the data from the FDA Tool and comment on any similarities or differences in the graphs. Is this what you expected? Can you make your m-file code efficient?

35%

C Insert noise into the input signal (you can choose the type of noise) then investigate and discuss the effect that the noise has on the filter input and out as a whole. Investigate the effect on the input and output plots of the filter and of the amplitude vs frequency graph.  How badly affected were the signals? Develop a methodology based to remove the noise from the signal justifying your choice of noise removal, stating which method was best and why? Does the noise removal affect the filter input and outputs and if so, how? Compare the original signal image with the noise removed signal, do they differ and if so, how? Increase the noise density to discover what the limit is that you can still remove the noise to obtain a signal within 90% of the original one. Modifications to the noise removal can be made to create more sophisticated and advanced processes in an attempt to remove this greater amount of noise. The higher the noise density removed, the more marks will be awarded, justification on the ordering and repetition of algorithms is still required at this stage. Investigate if such an algorithm could be implemented on a real world device.

35%D Write a concise report (marks will be deducted for unnecessary information) covering the details in Parts A – C.Keep the format of this similar as to that you would use in your Final Year Project dissertation. 10%

Your lab assignments are as published on CU Online. There are no classes for this coursework and you will be required to undertake your work independently. If you have any issues then please contact the module leader Dr Andrew Tickle. David Jones has since left the university and Shaun Yeates is not allocated to the resit coursework.
Keep a safe copy of all coursework submitted for reference.