Design and implement a 3-band equaliser using a DSP board or MPLab/CSS. The MATLAB Filter Designer could be used for filter design and graphing subject to the design requirements given below. This is an individual CW 2. Equaliser Primer An n-band equaliser is a device used to correct the frequency response characteristic of a signal processing system. Equalisers can be implemented using digital or analogue filters. The whole bandwidth of the equaliser is divided into n frequency bands, which can be individually amplified (a 3-band equaliser is shown in Figure 1). Thus, any desired frequency characteristic can be approximated. Very simple 3-band or 7-band equalisers are found in nearly every modern hi-fi system. Basically, an n-band equaliser is implemented using a low pass filter, a high pass filter and a set of n-2 band pass filters. Design three filters Low Pass High pass Band passSuggested requirements are as follows (Is this the best distribution for the filters? Refer to deliverable (f). Equalizer bandwidth: 23 kHz Low pass band: 0 8 kHz Band pass band: 8 15 kHz High pass band: 15 23 kHz Pass band ripple: max. 6% Stop band rejection min 38 dB Mild phase distortions are acceptable. The pass band ripples apply also to the combination of the three filters. It is expected that the frequency response of the 3 combined filters falls into a band of 0.94 to 1.06 (assuming a normalised response). To achieve this, it will be necessary to scale the individual filters. NB: The sampling frequency for this work is 48 KHz. 4. Design Hints Either finite impulse response filters (FIR) or infinite impulse response filters (IIR) can be used. When using FIR filters, any type of window can be used. However, it might be a good idea to think about a filter with a Hamming Window, a Hann Window or a Kaiser Window.
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Design a high pass FIR filter to meet the following specifications. Provide all equations needed to produce the filter's impulse response. Pass band: 14.66 - 22 kHz Stop band rejection: min 40 dB Pass band ripple: max. 5% Sampling frquency: 48 kHz Use either a Hamming, Hann or Kaiser window. Derive the first three filter coefficients.
Using the windowing functions discussed in class, design a low-pass FIR filter with a cutoff frequency of 2 kHz, a minimum stop band attenuation of 40 dB, and a transition width of 200Hz. The sampling frequency is 10kHz. 1. Using the windowing functions discussed in class, design a low-pass FIR filter with a cutoff frequency of 2 kHz, a minimum stop band attenuation of 40 dB, and a transition width of 200 Hz. The sampling frequency is 10 kHz 2....
DSP Lab Exercise 9 Given below are the Impulse Response h(n), of the four main types of FIR Digital filters. Use appropriate MATLAB expressions to find: a) System Response (H(z) b) Pole-zero diagram c) Amplitude Response d) Phase Response 1. FIR Low-Pass Digital Filter ,n= 0.1 |[d(n) + δ(n-I))-1 h(n) 0, otherwise 2. FIR High-Pass Digital Filter 0, otherwise 3. FIR Band-Pass Digital Filter 0, otherwise 4. FIR Band-Stop Digital Filter , n = 0,2 0, otherwise Note: Your final...
1. Design a custom FIR band-pass filter using the Fourier series and the Hanning window. The filter should be of order 8. We need to pass the signal in two audio bands 400-1600Hz and 4000-8000Hz and attenuate it elsewhere. The sampling frequency is 20 kHz. a) Calculate with pencil and paper the impulse response of the filter and the numerical values of the coefficients.
b) When designing a FIR filters, the impulse response of the ideal low-pass filter is usually modified by multiplying it by a windowing function such as the Hamming window which is defined, for an odd number N of samples, by: (2n)-(N-I)-ns(N-1) N-12 wlnl 0.54 + 0.46 cos i What are the advantages of windowing with this function compared 2 with a standard rectangular window? ii) Design a 10th Order Hamming windowed FIR low-pass filter with cut- off frequency at 1000...
4. a) The sequence x[n] is related to its discrete time Fourier transform (DTFT). Xeo), by the expression: 27T i) Use this expression to design a 10th order high-pass finite impulse response (FIR) filter with cut-off frequency of 7 kHz for signals sampled at 16 kHz. Perform your design using a rectangular window. ii State what improvement in the performance of the filter might be 3 obtained by the use of a Hamming window. iii) Sketch a direct form implementation...
a) The transfer function of an ideal low-pass filter is and its impulse response is where oc is the cut-off frequency i) Is hLP[n] a finite impulse response (FIR) filter or an infinite impulse response filter (IIR)? Explain your answer ii Is hLP[n] a causal or a non-causal filter? Explain your answer iii) If ae-0. IT, plot the magnitude responses for the following impulse responses b) i) Let the five impulse response samples of a causal FIR filter be given...
Please do both questions! thank you very much! (a) Does it have to be this way? Briefly explain, is it possible to have an online FIR filter without a window function? (b) Low-Pass Filter Consider the ideal impulse response of a low pass filter (of cut-off frequency given by hLP [n] = 0, sinc (odn-부) for a filter size N. Thus, hw InhnwHAM Now consider the case where N-100 and oc 0.3004. Determine hw, In] using the formula above. Then...
EE 448 Homework #6 1. Determine the impulse response, h(n), and plot the magnitude frequency response of each of the following FIR filters using the specified window methods. (25 pts) Low-pass filter having a cutoff frequency of /5, using the rectangular window and M-25 a. b. (25 pts) Low-pass filter having a cutoff frequency of z/5, using the Bartlett window and M=25 (25 pts) Low-pass filter having a cutoff frequency of /5, using the Hamming window and M-25 c. d....
Using the windowing function discussed in class, design a band pass FIR filter centered at 20 MHz with bandwidth 30MHz.. 3. Using the windowing functions discussed in class, design a band-pass FIR filter centered at 20 MHz with a bandwidth 30 MHz (), a minimum stop band attenuation of 30 dB, and a transition width of 1 MHz. The sampling frequency is 80 MHz, 3. Using the windowing functions discussed in class, design a band-pass FIR filter centered at 20...