scholarly journals The Theoretical Limits of Watermark Spread Spectrum Sequence

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Nan Jiang ◽  
Jian Wang
Keyword(s):  
Lower Bound ◽  
Spread Spectrum ◽  
Communication Channel ◽  
Cross Correlation ◽  
Digital Watermark ◽  
Correlation Property ◽  
Random Sequences ◽  
The Cross ◽  
Peak Correlation

At present, the spread spectrum (SS) sequences used in watermark include i.i.d. random sequences and the sequences used in SS communications. They appear earlier than digital watermark. Almost no researchers pay attention to whether they are really fit for watermark. In this paper, we compare the SS watermark channel and the traditional SS communication channel. We find out that their correlation property is different. Considering cropping and translation attacks, we define watermark auto- and cross-correlation and propose Loose Autocorrelation and Tight Cross-Correlation (LAC&TCC) properties for SS watermark. The LAC&TCC properties are that, whether or not synchronized, the autocorrelation is equal or close to 1 and the cross-correlation is equal or close to 0. Accordingly, the peak correlation is divided into the peak autocorrelationRa(l)and the peak cross-correlationRc(l). We establish the lower bound ofRc(l)and the higher bound ofRa(l), respectively. The two bounds indicate that, no matter how small the cover is reserved, the extractor can always find a threshold to distinguish auto- and cross-correlation in theory.

scholarly journals Modeling Complex System Correlation Using Detrended Cross-Correlation Coefficient

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Keqiang Dong ◽  
Hong Zhang ◽  
You Gao
Keyword(s):  
Complex System ◽  
Time Series ◽  
Correlation Coefficient ◽  
Cross Correlation ◽  
Heavy Tails ◽  
Correlation Property ◽  
Traffic Time Series ◽  
Cross Correlations ◽  
The Cross ◽  
Active Research

The understanding of complex systems has become an area of active research for physicists because such systems exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails, and fractality. We here focus on traffic dynamic as an example of a complex system. By applying the detrended cross-correlation coefficient method to traffic time series, we find that the traffic fluctuation time series may exhibit cross-correlation characteristic. Further, we show that two traffic speed time series derived from adjacent sections exhibit much stronger cross-correlations than the two speed series derived from adjacent lanes. Similarly, we also demonstrate that the cross-correlation property between the traffic volume variables from two adjacent sections is stronger than the cross-correlation property between the volume variables of adjacent lanes.

Comparative Study on Spreading Codes

2017 ◽  
Vol MCSP2017 (01) ◽  
pp. 14-16
Author(s):  
Omprava Agasti ◽  
Sujatarani Raut ◽  
Shibashis Pradhan
Keyword(s):  
Communication Networks ◽  
Spread Spectrum ◽  
Cross Correlation ◽  
Additive White Gaussian Noise ◽  
Personal Communication ◽  
Spreading Codes ◽  
Personal Communication Networks ◽  
Transmission Data ◽  
Commercial Applications ◽  
Spread Spectrum Systems

In this paper, we studied on spreading code for wireless communication, their performance analysis, applications and its implementation. Spread-spectrum systems have found important commercial applications in CDMA cellular networks and wireless personal communication networks. Implementation is complex, mainly because spreading the baseband (by a factor that can be several orders of magnitude) forces the electronics to act and react accordingly, which, in turn, makes the spreading and dispreading operation necessary. In spread spectrum the transmission signal bandwidth is much higher than the information bandwidth. The signal occupies a bandwidth much larger than what is necessary to send the information in spread spectrum technology. CDMA uses unique spreading codes to spread the baseband data before transmission data. The performance of a CDMA system gets controlled by two types of interference, namely ISI and MAI which are the function of auto and cross correlation values of the spreading codes respectively. The existing codes using Additive White Gaussian Noise channel under multi-user has been compared with the Bit Error Rate(BER) performance.

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.

scholarly journals Detection and Localization for Multiple Stationary Human Targets Based on Cross-Correlation of Dual-Station SFCW Radars

2019 ◽  
Vol 11 (12) ◽  
pp. 1428 ◽  
Author(s):  
Yong Jia ◽  
Yong Guo ◽  
Chao Yan ◽  
Haoxuan Sheng ◽  
Guolong Cui ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Continuous Wave ◽  
Coefficient Matrix ◽  
Constant False Alarm Rate ◽  
Localization Algorithm ◽  
Cfar Detection ◽  
Stepped Frequency ◽  
The Cross ◽  
The One ◽  
Detection And Localization

This paper demonstrates the feasibility of detection and localization of multiple stationary human targets based on cross-correlation of the dual-station stepped-frequency continuous-wave (SFCW) radars. Firstly, a cross-correlation operation is performed on the preprocessed pulse signals of two SFCW radars at different locations to obtain the correlation coefficient matrix. Then, the constant false alarm rate (CFAR) detection is applied to extract the ranges between each target and the two radars, respectively, from the correlation matrix. Finally, the locations of human targets is calculated with the triangulation localization algorithm. This cross-correlation operation mainly brings about two advantages. On the one hand, the cross-correlation explores the correlation feature of target respiratory signals, which can effectively detect all targets with different signal intensities, avoiding the missed detection of weak targets. On the other hand, the pairing of two ranges between each target and two radars is implemented simultaneously with the cross-correlation. Experimental results verify the effectiveness of this algorithm.

MULTIFRACTAL DETRENDED CROSS-CORRELATION ANALYSIS FOR LARGE-SCALE WAREHOUSE-OUT BEHAVIORS

Fractals ◽  
2015 ◽  
Vol 23 (04) ◽  
pp. 1550044 ◽  
Author(s):  
CAN-ZHONG YAO ◽  
JI-NAN LIN ◽  
XU-ZHOU ZHENG
Keyword(s):  
Correlation Analysis ◽  
Large Scale ◽  
Cross Correlation ◽  
Correlation Property ◽  
Long Term Memory ◽  
Correlation Relationship ◽  
Term Memory ◽  
Wire Rod ◽  
Cross Correlation Analysis

Based on cross-correlation algorithm, we analyze the correlation property of warehouse-out quantity of different warehouses, respectively, and different products of each warehouse. Our study identifies that significant cross-correlation relationship for warehouse-out quantity exists among different warehouses and different products of a warehouse. Further, we take multifractal detrended cross-correlation analysis for warehouse-out quantity among different warehouses and different products of a warehouse. The results show that for the warehouse-out behaviors of total amount, different warehouses and different products of a warehouse significantly follow multifractal property. Specifically for each warehouse, the coupling relationships of rebar and wire rod reveal long-term memory characteristics, no matter for large fluctuation or small one. The cross-correlation effect on long-range memory property among warehouses probably has less to do with product types,and the long-term memory of YZ warehouse is greater than others especially in total amount and wire rod product. Finally, we shuffle and surrogate data to explore the source of multifractal cross-correlation property in logistics system. Taking the total amount of warehouse-out quantity as example, we confirm that the fat-tail distribution of warehouse-out quantity sequences is the main factor for multifractal cross-correlation. Through comparing the performance of the multifractal detrended cross-correlation analysis (MF-DCCA), centered multifractal detrending moving average cross-correlation analysis (MF-X-DMA) algorithms, the forward and backward MF-X-DMA algorithms, we find that the forward and backward MF-X-DMA algorithms exhibit a better performance than the other ones.

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