FIR Filter Design Using Modified Lanczos Window Function

2012 ◽  
Vol 566 ◽  
pp. 49-56
Author(s):  
Md. Abdus Samad ◽  
Jia Uddin ◽  
Md. Razu Ahmed

Attenuated side lobe peak in the range of around ~-45dB is required in many applications of signal processing and measurements. However, the problem is usual window based FIR filter design lies in its side lobes amplitudes that are higher than the requirement of application. We propose a modified Lanczos window function by heuristic by examining the Lanczos window, which has better performance like equiripple, minimum side lobe compared to the several commonly used windows. The proposed window has slightly larger main lobe width of the commonly used Hamming window, while featuring 5.1~18.5 dB smaller side lobe peak. The proposed modified Lanczos window maintains its maximum side lobe peak about -55.2~-51.9 dB compared to -39~-36.7 dB of Hamming window for M=10~14, while offering roughly equal main lobe width. Our simulated results also show significant performance upgrading of the proposed modified Lanczos window compared to the Kaiser, Gaussian, and Lanczos windows. The proposed modified Lanczos window also shows better performance than Dolph-Chebyshev window. Finally, the example of designed low pass FIR filter confirms the efficiency of the proposed modified Lanczos window.

2019 ◽  
Vol Volume-3 (Issue-3) ◽  
pp. 518-520
Author(s):  
M. Santhanaraj ◽  
Rishikesh. S. S ◽  
Subramanian. A. N | Vijai Sooriya. Su ◽  

2014 ◽  
Vol 05 (03) ◽  
pp. 57-67 ◽  
Author(s):  
Mudit Shukla ◽  
G. R. Mishra

2014 ◽  
Vol 556-562 ◽  
pp. 3703-3706
Author(s):  
Le Qiang Bai ◽  
Xue Wei Zhang

In view of spectrum leakage and the contradictory problem of spectrum accuracy of main lobe and reducing spectrum leakage, MFCC algorithm based on improved window function is proposed. Improved window function is based on the mathematical analysis of Kaiser window, and under the condition of finite sampling points minuses weighted impact function where is at the frequencies that side lobe peaks of correspond to. The amplitude of improved window compared with Kaiser window is smaller, and main lobe width is the same, solving the conflicting problem of main lobe width and side lobe amplitude and reducing spectrum leakage. The experimental results show that speech recognition rate of MFCC feature parameter extraction algorithm based on improved window function is better than Kaiser window and Hamming window.


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