6.

Latticesemi.com. (2018). ???? LatticeECP3 Versa Development Kit @latticesemi ????????????. online Available at: http://www.

latticesemi.com/ecp3versaAccessed 21 Jan. 2018.

5. Ti.com.

(2018). Cite a Website – CiteThis For Me. online Available at:http://www.ti.com/lit/ds/symlink/tms320c6748.pdf Accessed 21 Jan.

2018.4. Ti.com.

(2018). TMDXLCDK6748 TMS320C6748DSP Development Kit (LCDK) | TI.com. online Available at:http://www.ti.com/tool/TMDXLCDK6748 Accessed 21 Jan. 2018.

3. Dsp-book.narod.ru.

(2018). Cite a Website- Cite This For Me. online Available at: http://dsp-book.

narod.ru/RTDSP.pdfAccessed 21 Jan. 2018.2. Anon, (2018). online Available at:http://www.electronics-tutorials.

ws/filter/band-stop-filter.html Accessed 21Jan. 2018.1. Ens.

ewi.tudelft.nl. (2018). Cite aWebsite – Cite This For Me.

online Available at:http://ens.ewi.tudelft.nl/Education/courses/et2405/notes/champagne04.pdfAccessed 21 Jan. 2018.References · LatticeECP3 FPGA: LFE3-35EA-8FN484C, has a 64-Mbit SPI Flash Memory, 1 Gbit DDR3, PCIExpress x1 interface, 4 SMA connectors for electrical testing of onefull-duplex SERDES channel, 2 RJ45 interfaces to 10/100/1000 Ethernet to GMII, Extensionconnectors used for prototyping, 14-segment alpha-numeric display, Switches,LEDs, and display for demo purposes, Push-buttons for common purpose I/O andreset, on board reference clock sources, Programmed using a mini USB cable viaPCROHS compliant. Features:2.

LatticeECP3 Versa Development Kit · Dspsubsystem involves: C674x DSP CPU, 32KB L1 program/cache up to 32KB etc. · Thisis code suitable with the C6000.· Theconnectivity and storage of the standard interface allow the audio, video, andother signal on the board. Communications, audio,biometric analytics, real time signal etc.

1. TMS320C6748:an expandable program that doesn’t allow the advancement of applications thatinvolve:Twocurrent dsp development kits: · Complexity· Reliability· Flexibility· ReproducibilityBesidesthe common analogue devices, modulators, amplifiers and filters there are othervarious advantages in using digital techniques for signal processing: Nonreal time and real time are two types of digital signal processing application.In digital signal processing systems there are limitations like the bandwidth,memory etc.

Unlikethe analogue systems, Dsp systems deliver the exact solution given the exactinput and materials will not affect the operation of the system. Digital signal processing is involved with thedigital description of signals and the use of digital hardware to inspect,alter, or obtain materials from these signals. The system is simple toestablish, examine, assess. The system is expensive to construct. 4)provide a comprehensive discussion on design consideration that are needed, ifa real-time DSP system were employed.

Comment on at least TWO current DSPdevelopment kits (available in UK), for audio processing. thisproves that the cut off frequency is recognised, it is used to keep the lowerfrequency. F2 has been filtered out. Itdisplays both frequencies. A low pass filter is used to remove the larger frequencies.Goto options, click on magnitude scale and select linear. It should display Toview in frequency under spectra>create> method:FFT> apply, and itshows on decibels.Thesystem displays a signal browser that shows the wave in time.

Thefrequency response must be normalized to display the output. The software has afunction that shortens the input, and it creates the output. Cutoff frequency should be higher that F1 and lower that F2. Cut off frequency is500.thesample frequency(Fs) should be five times greater than the largest frequencywhich is F2 therefore Fs=3000. F2=600F1=360 Createa new script file in MATLAB, copy filter implementation code from Moodle andinsert the frequencies: 3)write a programme using MATLAB that filters specified frequencies from a giveninput signal.

Each student will receive information in scheduled sessionsregrading: unique input signal and which frequencies are to be filtered. Thissystem is a stopband filter. This filter transfers all frequencies with the exemptionof those in a definite stop band which are significantly attenuated. ifw= ifw=ifw=0 iv. Determinethe type of filter and prove your result. bychanging to , the frequency response can be determined. substitutez in the place of n. to make it a Z function iii.

Determinethe transfer function and frequency response. · Thefunction is FIR. ii. Determinewhether filter is FIR or IIR. i. Sketchthe structure for the filter. 2)A FIR filter is described by the following difference equation. thereare no frequencies components of the input signal that have been attenuated bythe filter.

therefore III. Explainwhich frequencies components of the input signal have been attenuated by thefilter. x x x Theoutput recovered is: Replace with Thiscan be simplified to II. Calculatethe output yn recovered, using the input x(t) and H(Z).

= 40?t and 80?t. Substitute T with N, divide the f’s by 2. I. Determinethe discrete signal, x(t) 1b)the input applied to the system in Q1) will be the discrete version offollowing continuous time signal. Assume the following sample frequency, Fs =400 Hz. Thecut off frequency is at -56.

70, which is 6.13 KHz. IV. Determineand label the following values onto the filter response: passband, transitionband, maximum gain and cut III. Plotthe poles and zero using the signal processing tool (spool) in MATLAB. thisshows that the signal is causal because the poles are inside the unit circle. Stabilitycriteria: the absolute sum from – ? to +?must be less than infinity. causal:if the amplitude of the signals are zero when ‘n’ is less than ‘0’ (n<0)then the signal is said to be causal.

Therefore: R.O.C– region of frequency spectrum where the domain exists.

InverseZ transform using stipulation of partial fraction expansion. II. Determineand explain the stability and causality properties. poles:zero,Z=0 Zero ‘0’: a value of Z, when substituted makes Z transform to 0. Poles ‘X’: a value of Z, when substituted into a Z transform will go toinfinity.

I. Determine the poles and zeros 1a)For the following linear time invariant transfer function H(Z) which representsa filtering system.Part A