Elliptical function based differential band pass filter for IF signal processing and EMI applications

2015 ◽  
Author(s):  
M Srinivasa Rao ◽  
I Mahalakshmi ◽  
K Mourougayane
Keyword(s):  
Signal Processing ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Band Pass ◽  
Elliptical Function

Design and Realization of FIR Band-Pass Digital Filter Based on MATLAB

2012 ◽  
Vol 503-504 ◽  
pp. 228-231 ◽  
Author(s):  
Shan Ren ◽  
Xin Zhao ◽  
Jie Jiang ◽  
Dong Jin Zhao
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Filter ◽  
Digital Signal ◽  
Window Function ◽  
Measured Signal ◽  
Time Interval ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Band Pass

Digital filter is one of the most important parts of digital signal processing. In practice, digital signal processing often need to limit the signal observation time interval within a certain time, choose only one period of signal that signal data will be truncated, this process is equivalent to plus window function operation to signal. In order to obtain finite unit sample response, need to truncate the infinite unit sample response sequence by window function. This paper proposes the method of using window function to design FIR Band-pass filter based on MATLAB, according to the design basic principle of FIR digital filter. Filtering processing for measured signal showed that filtering effect of the filter achieved the expected results.

Continuously time‐variable recursive digital band‐pass filters for seismic signal processing

Geophysics ◽  
1983 ◽  
Vol 48 (6) ◽  
pp. 702-712 ◽  
Author(s):  
R. A. Stein ◽  
N. R. Bartley
Keyword(s):  
Signal Processing ◽  
Seismic Signal ◽  
Time Variable ◽  
Band Pass Filter ◽  
Worst Case ◽  
Pass Filter ◽  
Time Direction ◽  
Low Pass ◽  
Band Pass ◽  
Seismic Signal Processing

A design technique is described for continuously time‐variable recursive digital band‐pass filters for seismic signal processing. Two types of band‐pass filters are considered: a cascade of a low‐pass and a high‐pass filter, and a direct band‐pass filter, with all filters being derived from a continuous unit‐bandwidth Butterworth low‐pass prototype. Linear interpolation of the filter coefficients between points at which they are known exactly is used to reduce the computational overhead. Data are given for determining the length of the interpolation interval to meet prescribed worst case magnitude and frequency error criteria. A zero‐phase response is achieved by filtering in the forward time direction followed by filtering in the reverse time direction. An example is included.

Matlab Implementation in ZOOM FFT Technology Based on Analytic Signal and Band-Pass Filter

2015 ◽  
Vol 733 ◽  
pp. 922-925
Author(s):  
Yu Qing Zhao ◽  
Yong Hua Zhang ◽  
Yue Zhang
Keyword(s):  
Signal Processing ◽  
Frequency Characteristic ◽  
Virtual Instrument ◽  
Characteristic Curve ◽  
Analytic Signal ◽  
Frequency Resolution ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Band Pass ◽  
Matlab Implementation

ZOOM FFT technology is widely used in signal processing and modal analysis, it can improve frequency resolution, and amplify the characteristic curve in selected regions, makes the frequency characteristic of the system more clearly shown. ZOOM FFT technology based on analytic signal and band-pass filter has greatly improved than traditional methods, provides a new way to virtual instrument based on computer platform. This article discusses the application of Matlab to achieve the ZOOM FFT.

Signal Processing In Transmission Fluctuation Spectrometry With Band-Pass Filter

2007 ◽  
Author(s):  
Jianqi Shen ◽  
Yamin Xu ◽  
Bin Yu ◽  
Xiaoai Guo ◽  
Ulrich Riebel
Keyword(s):  
Signal Processing ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Band Pass

OBSERVATION AND SIMULATION OF TSUNAMIS INDUCED BY THE 2003 TOKACHI-OKI EARTHQUAKE (M 8.0)

2015 ◽  
Vol 2 (3) ◽  
Author(s):  
Tatsuo Ohmachi ◽  
Shusaku Inoue ◽  
Tetsuji Imai
Keyword(s):  
Rayleigh Wave ◽  
Water Pressure ◽  
Near Field ◽  
Source Region ◽  
Tsunami Source ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Tsunami Simulation ◽  
Sea Bed ◽  
Band Pass

The 2003 Tokachi-oki earthquake (MJ 8.0) occurred off the southeastern coast of Tokachi, Japan, and generated a large tsunami which arrived at Tokachi Harbor at 04:56 with a wave height of 4.3 m. Japan Marine Science and Technology Center (JAMSTEC) recovered records of water pressure and sea-bed acceleration at the bottom of the tsunami source region. These records are first introduced with some findings from Fourier analysis and band-pass filter analysis. Water pressure disturbance lasted for over 30 minutes and the duration was longer than those of accelerations. Predominant periods of the pressure looked like those excited by Rayleigh waves. Next, numerical simulation was conducted using the dynamic tsunami simulation technique able to represent generation and propagation of Rayleigh wave and tsunami, with a satisfactory result showing validity and usefulness of this technique. Keywords: Earthquake, Rayleigh wave, tsunami, near-field

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