Spectral Analysis of Shadow Filters

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Spectral Analysis of Shadow Filters *P.Krishna Rao, **T.Sandhya Devi, **S.Lalitha Kumari, **T.suryaprakash, **D.Dinesh. *Asst.prof, ** Students, ECE Department, SSCE, Srikakulam.

1 Spectral Analysis of Shadow Filters *P.Krishna Rao, **T.Sandhya Devi, **S.Lalitha Kumari, **T.suryaprakash, **D.Dinesh. *Asst.prof, ** Students, ECE Department, SSCE, Srikakulam. Abstract - It is shown that the Shadow filter, to study and discuss the characteristics of the new concept of shadow filters introduced recently by Lakys and Fabre. The proposed combination are Low pass filter(lpf) in main path and High pass filter, Band pass filter, Band stop filter are in Feedback path and second one in HPF in main path, LPF BPF,BSF in Feedback path, third one is BPF in main path, LPF,HPF,BSF in Feedback path. These LPF, HPF, BPF, BSF are consider from both Infinite impulse response and Finite impulse response filter. We analyze the characteristic features, in various points and at different localization levels with multiple filters. In this attempt the proposed shadow filters receives better SNR values than the existing basic filter i.e. in main path filter. Index Terms Shadow filters, FIR and IIR filters. I. INTRODUCTION In a recent paper, Lakys [1,2] and Fabre [5,6] introduced a new filters, called, Shadow Filters for electronically tuning the characteristics of a basic filters. Further shadow filters extended by S. C. Dutta Roy [3]. A general block diagram of the scheme is shown Fig.1, in which the authors of consider H(s) to be a low pass filter while H 1 (s) is a band pass or high pass or band reject function, both being of first order with same denominator. They shows that thereby the characteristics of the modified transfer function is as H(s) = V o/ V in retains the low pass characteristic, but with variable sideband attenuation that the bandwidth remains the constant. importance can be obtained. The organization of this paper as follows: the second section explains the basic structure of shadow concept, section 3 reviles about the different types of filters and the last chapter explains the results of the proposed filters. The characteristics of the shadow filters by using IIR and FIR filters can be obtained. Finally a suggestion is made for the design of a simple but interesting experiment for undergraduate students, using only by FIR, and IIR filters and how the shadow technique can be used to improve their quality. II. ANAYSIS Consider a basic filter, which can IIR or FIR, which is capable of realizing any of the four possible characteristics viz. low pass, high pass, band pass, band stop or a combination of these. Such realization can, for example, be a sample combination of filter. Here, the feedback factor is taken for better output. Thus consider a low pass filter, as shown Fig.2 below Figure 2: example of Shadow filter Lpf* is low pass shadow filter Figure 1: Basic second order filters The purpose of this paper is to make more general analysis of the scheme and to demonstrate that by properly choosing H(s) and H 1 (s), various types of interesting characteristics of practical Lpf = lpf (1 ± β. lpf) Lpf = lpf (1 ± β. hpf) Lpf = lpf (1 ± β. bpf) 461

2 Lpf = lpf (1 ± β. bsf ß is feedback parameter, ß= [0, 1] Similarly as low pass filter we can illustrate band pass, high pass, band reject filters also. Shadow filters is used for filtering applications, to perform the frequency selection is called a filter. III. SPECIAL CASE We already discussed that by using shadow filters e can improve the SNR value of a signal than the basic signal. Here there is special case to increase the SNR is combinational windows. These widows are improving the quality of a signal. For example consider hamming window in shadow filter, then we add the hanning or Kaiser to the hanning widow then we get better SNR than using single widow called it as combinational window. Combinational windows: w(n)= hanning(n)+hamming(n) w(n)= hanning(n)+kaiser(n,7) w(n)=kaiser(n,7)+hamming(n) IV. CHARACTERSTICS Filters are used to oppose unwanted signals and allow wanted signals. FILTERS 4.1 FIR & IIR FILTERS: The terms finite impulse response (FIR) & infinite impulse response (IIR) are used to distinguish digital filter types. The FIR filters are non recursive type, whereas IIR filters are of recursive type. 4.2 LOWPASS FILTER: This allows the low signals frequencies and opposes high frequency signals. 4.3 HIGH PASS FILTER: This allows the high frequency signals and opposes low frequency signals. 4.4 BAND REJECT FILTER: This opposes particular frequencies and allows remaining signals. 4.5 BAND PASS FILTER: This allows particular or desired frequencies, and allows remaining frequencies. 4.6 WINDOW METHOD: Which are infinite Fourier series available in FIR filters so there is very difficult to transmit, so used truncation but while using there is oscillations produced in that. So these phenomena called the GIBB S PHENOMENAN. To overcome this window method used. 4.7 Types of windows: IIR FIR WINDOW METHOD 1. Rectangular window 2. Hanning window 3. Hamming window 4. Kaiser window BUTTERWORTH CHEBYSHEV 1. LPF 1.TYPE 1 2. HPF 2.TYPE 2 3. BPF 4. BRF In this we used window methods in FIR filters and where as in IIR filters, Butterworth and Chebyshev. In this paper four windows also used to get better purity. The shadow filter characteristics same as the basic filter characteristics, as shown below Fig.3 462

Figure 4: lpf+hamming window without feedback Figure 3: characteristics of filter In the above fig. there are 1. Side lobe fan off ratio [SLFR] 2. Half main lobe width [HMLW] 3.

The central lobe of frequency response of the window should contain most of energy and should be narrow. 2. The higher side lobe level of the frequency response should be small. 3.

3 Figure 4: lpf+hamming window without feedback Figure 3: characteristics of filter In the above fig. there are 1. Side lobe fan off ratio [SLFR] 2. Half main lobe width [HMLW] 3. Side lobe attenuation [SLA] Figure 5: lpf+hamming β= 0.1 feedback Therefore, the window, chosen the truncating the infinite impulse response should have some desirable characteristics they are: 1. The central lobe of frequency response of the window should contain most of energy and should be narrow. 2. The higher side lobe level of the frequency response should be small. 3. The side lobes of the frequency response should decrease in energy rapidly has w tends to π. V. RESULTS Consider an example that low pass filter and take feedback factor β as [0, 1] and then by hamming window in FIR filters we get these results. The sideband attenuation will be decreased in shadow filter than basic filter, if we increasing the feedback factor value we get better out, means the data stored in main lobe only due to more strength in it. Figure 6: lpf+hamming β= 0.2 feedback Table1: Lpf with hamming widow results Feedback MSLA(dB) HMLB(dB) factor(β)

VERIFICATION: If we very this filter to a sine signal with the signal is a 100-Hz sine wave in additive N (0, 1/4) white

Then it is feedback to the low pass filter with hammig window the SNR values and graphs are as below: Figure 10: lpf+ hamming

4 Table 2: Lpf +hamming Snr for shadow filters: Figure 8: noise signal Feedback factor(β) SNR --- 7.03 0.01 7.0745 0.1 7.44 0.

CONCLUSION Figure 9: noise+sinusoidal signal The versatility of an interesting shadow filter, which can be electronically

4 VERIFICATION: If we very this filter to a sine signal with the signal is a 100-Hz sine wave in additive N (0, 1/4) white Gaussian noise. Set the random number generator to the default state for reproducible results. Then it is feedback to the low pass filter with hammig window the SNR values and graphs are as below: Figure 10: lpf+ hamming with β=0.1 Figure 7: sinusoidal signal Figure 11: lpf+ hamming with β=0.4 Table 2: Lpf +hamming Snr for shadow filters: Figure 8: noise signal Feedback factor(β) SNR VI. CONCLUSION Figure 9: noise+sinusoidal signal The versatility of an interesting shadow filter, which can be electronically tuned by varying the gain of an amplifier, has been discussed in this paper. The advantages of shadow filters is same as filters but it get better quality and it can be quickly understandable for experimentation and self learning by the students. 464

5 VII. REFRENCES [1] Y.Lakys, and A. Fabre, shadow filter-a new family of second order filters, electronics letter, vol 46, No. 4, pp , engineering,srikakulam, INDIA, ph no: [2] Lakys, Y., Godara, B., Fabre, A.: `Cognitive and encrypted communications. Part 2: a new theory for frequency agile active filters and the validation results for an agile band pass in SiGe-BiCMOS', Invited paper, 6th Int. Conf. on Electrical and Electronics Engineering, ELECO 2009, November 2009, Bursa, Turkey, p [3] S.C. Dutta Roy, The many faces of the single tuned circuit, IETE journal of education, vol 41, NO. 4, PP , [4] N. J. Fliege, Multiple biquads, ch. 13 in The circuits and Filters Handbook, W.K.chen(Ed), 2007, CRC Press. [5] Fabre, A., Saaid, O., Wiest, F., Boucheron, C.: `High frequency applications based on a new current controlled conveyor', IEEE Trans. Circuits Syst., 1996, 43, p [6] Fabre, A.: Electronique analogique rapide, circuits et applications, 2009 (TechnoSup, Ellipses edit.paris, France) Authors: 1. P.Krishna Rao, assistant professor,sri svani college of engineering, srikakulam, INDIA, ph no T.Sandhya devi, student of electronics engineering,srikakulam, INDIA, ph no: S.Lalitha kumari, student of electronics engineering, srikakula, INDIA, ph no: T. Suryaprakash, student of electronics 465

FIR FILTER DESIGN USING NEW HYBRID WINDOW FUNCTIONS

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