scholarly journals Preliminary analog-computer study of the cross-correlation impulse-response measurement techniques to determine optimum input-signal characteristics

1964 ◽  
Author(s):  
E.K. Honka ◽  
G.H. Steiner
Keyword(s):  
Impulse Response ◽  
Input Signal ◽  
Cross Correlation ◽  
Measurement Techniques ◽  
Analog Computer ◽  
Computer Study ◽  
Response Measurement ◽  
Signal Characteristics ◽  
The Cross ◽  
Optimum Input

AN ANALOG SEISMlC CORRELATOR

Geophysics ◽  
1961 ◽  
Vol 26 (3) ◽  
pp. 298-308 ◽  
Author(s):  
F. N. Tullos ◽  
L. C. Cummings
Keyword(s):  
Seismic Data ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Analog Computer ◽  
Signal Power ◽  
Arrival Times ◽  
Data Points ◽  
The Cross ◽  
Correlation Process ◽  
Total Average

An analog computer has been built to compute the cross‐correlation coefficients of multi‐trace seismograms. The evaluation program has shown that the computer has greater accuracy than is normally required to compute the cross‐correlation functions of short samples of data. Points on the correlation curves are computed and plotted at the rate of approximately 50 points per minute. Scanning is in difference of arrival times (Δt) across the record, with increments of [Formula: see text] to 16 millisecond. The correlation process is completely automatic with the exception of normalization, which is approximated by holding the total average signal power constant with a ganged attenuator. Analysis of synthetic and actual seismic data indicates that the correlation will be an interpretational aid in areas where the data are poor.

A variable‐step size NLMS algorithm based on the cross‐correlation between the squared output error and the near‐end input signal

2019 ◽  
Vol 14 (8) ◽  
pp. 1197-1202
Author(s):  
Fausto Casco‐Sanchez ◽  
Miguel Lopez‐Guerrero ◽  
Sergio Javier‐Alvarez ◽  
Reyna Carolina Medina‐Ramirez
Keyword(s):  
Input Signal ◽  
Cross Correlation ◽  
Variable Step Size ◽  
Step Size ◽  
Output Error ◽  
Nlms Algorithm ◽  
Variable Step ◽  
The Cross

Biosignal Denoising Techniques

2018 ◽  
pp. 26-37
Author(s):  
Suchetha M. ◽  
Jagannath M.
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Adaptive Filter ◽  
Input Signal ◽  
Adaptive Filters ◽  
Dynamic Variations ◽  
Signal Characteristics ◽  
Unknown System ◽  
Representation Method ◽  
Response To Change

The main aim of ECG signal enhancement is to separate the required signal components from the unwanted artifacts. Adaptive filter-based ECG enhancement helps in detecting time varying potentials and also helps to track the dynamic variations of the signals. LMS-based adaptive recurrent filter is used to obtain the impulse response of normal QRS complexes. It is also used for arrhythmia detection in ambulatory ECG recordings. Adaptive filters self-modify its frequency response to change the behavior in time. This property of adaptive filter allows it to adapt its response to change in the input signal characteristics. A major problem in adaptive filtering is the computational complexity of adaptive algorithm when the unknown system has a long impulse response and therefore requires a large number of taps. The wavelet transform is a time-scale representation method with a basis function called mother wavelet. In wavelet transform, the input signal is subsequently decomposed into subbands. Wavelet transform thresholding in the subband gives better performance of denoising.

A METHOD OF DETERMINING CROSS-CORRELATION COEFFICIENTS OF TIME-VARYING SIGNALS

1966 ◽  
Vol 44 (2) ◽  
pp. 415-422
Author(s):  
F. H. Palmer ◽  
G. F. Lyon
Keyword(s):  
Correlation Coefficient ◽  
Input Signal ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Time Varying ◽  
Pulse Counting ◽  
Pulse Trains ◽  
The Cross

Pulse-counting techniques allow the cross-correlation coefficient between two time-varying signals to be rapidly evaluated, if the two signals are first converted to pulse trains whose repetition frequencies are proportional to the respective amplitudes. Equipment using this technique is described. Estimates are given of the overall accuracy of the device for various types of input signal and for various signal durations. Provided the depth of modulation of the signals is over 50%, their cross-correlation coefficient may be determined to an accuracy of ± 0.05 for sample lengths of 2 minutes. The application of the system to the determination of cross-correlation coefficients of v.h.f. forward-scattered signals received on spaced antennae is also described.

scholarly journals Insights to enhance the examination of tool marks in human cartilage

2021 ◽  
Author(s):  
Matthias Weber ◽  
Anja Niehoff ◽  
Markus A. Rothschild
Keyword(s):  
Light Microscope ◽  
Cross Correlation ◽  
Costal Cartilage ◽  
Correlation Coefficients ◽  
Human Cartilage ◽  
Cut Marks ◽  
Tool Marks ◽  
The Cross ◽  
Cleaning Methods ◽  
The Individual

AbstractThis work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibres leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

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