Quantum watermarking algorithm based on chaotic affine scrambling

2019 ◽  
Vol 17 (04) ◽  
pp. 1950038
Author(s):  
RiGui Zhou ◽  
YouDe Cheng ◽  
Hou Ian ◽  
XingAo Liu
Keyword(s):  
Signal To Noise Ratio ◽  
Visual Quality ◽  
Extraction Process ◽  
Watermark Image ◽  
Signal To Noise ◽  
Quantum Watermarking ◽  
Embedding Strategy ◽  
Simulation Results ◽  
Color Value ◽  
Carrier Image

In order to improve the security of watermark image, a scheme of quantum watermarking algorithm which is based on chaotic affine scrambling is proposed and it includes scrambling, embedding and extracting procedures. In the embedding process, the position and the color of the watermark image are scrambled by chaotic affine and the size of the scrambled watermark image is extended from [Formula: see text] to [Formula: see text]. Meanwhile, the color value of the pixel is changed from 24-bits to 3-[Formula: see text](1-bit per channel) bits. The extended watermark image is embedded into the carrier image through a two-bit embedding strategy, and the extraction process is the inverse one of the embedding process. The simulation results show that the proposed scheme is superior to the comparison scheme in terms of visual quality, peak signal-to-noise ratio (PSNR).

scholarly journals Cooperative Spectrum Sensing Based on Convolutional Neural Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4440
Author(s):  
Youheng Tan ◽  
Xiaojun Jing
Keyword(s):  
Neural Networks ◽  
Spectrum Sensing ◽  
Convolutional Neural Networks ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Majority Voting ◽  
Signal To Noise ◽  
Hidden Terminal ◽  
Simulation Results ◽  
Sensing Performance

Cooperative spectrum sensing (CSS) is an important topic due to its capacity to solve the issue of the hidden terminal. However, the sensing performance of CSS is still poor, especially in low signal-to-noise ratio (SNR) situations. In this paper, convolutional neural networks (CNN) are considered to extract the features of the observed signal and, as a consequence, improve the sensing performance. More specifically, a novel two-dimensional dataset of the received signal is established and three classical CNN (LeNet, AlexNet and VGG-16)-based CSS schemes are trained and analyzed on the proposed dataset. In addition, sensing performance comparisons are made between the proposed CNN-based CSS schemes and the AND, OR, majority voting-based CSS schemes. The simulation results state that the sensing accuracy of the proposed schemes is greatly improved and the network depth helps with this.

An Improved Acquisition Method for High-Order BOC-Modulated Signals Based on Fractal Geometry

2013 ◽  
Vol 846-847 ◽  
pp. 1185-1188 ◽  
Author(s):  
Hua Bing Wu ◽  
Jun Liang Liu ◽  
Yuan Zhang ◽  
Yong Hui Hu
Keyword(s):  
Fractal Geometry ◽  
Output Signal ◽  
Signal To Noise Ratio ◽  
High Order ◽  
Main Peak ◽  
Signal To Noise ◽  
Binary Offset Carrier ◽  
Simulation Results ◽  
Modulated Signals ◽  
Acquisition Method

This paper proposes an improved acquisition method for high-order binary-offset-carrier (BOC) modulated signals based on fractal geometry. We introduced the principle of our acquisition method, and outlined its framework. We increase the main peak to side peaks ratio in the BOC autocorrelation function (ACF), with a simple fractal geometry transform. The proposed scheme is applicable to both generic high-order sine-and cosine-phased BOC-modulated signals. Simulation results show that the proposed method increases output signal to noise ratio (SNR).

scholarly journals Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Gustavo Asumu Mboro Nchama ◽  
Angela Leon Mecias ◽  
Mariano Rodriguez Ricard
Keyword(s):  
Image Processing ◽  
Mean Absolute Error ◽  
Signal To Noise Ratio ◽  
Visual Quality ◽  
Absolute Error ◽  
Natural Images ◽  
Mean Square ◽  
Signal To Noise ◽  
Major Drawback ◽  
Diffusivity Function

The Perona-Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this model has a major drawback: it tends to make the image look blocky. This work proposes to modify the PM model by introducing the Caputo-Fabrizio fractional gradient inside the diffusivity function. Experiments with natural images show that our model can suppress efficiently the blocky effect. Also, our model has good performance in visual quality, high peak signal-to-noise ratio (PSNR), and lower value of mean absolute error (MAE) and mean square error (MSE).

Highly Accurate Frequency Interpolation of Apodized FFT Magnitude-Mode Spectra

1998 ◽  
Vol 52 (1) ◽  
pp. 134-138 ◽  
Author(s):  
Yutaka Goto
Keyword(s):  
Simple Formula ◽  
Previous Investigation ◽  
Signal To Noise Ratio ◽  
Damping Ratio ◽  
Frequency Error ◽  
Signal To Noise ◽  
Window Functions ◽  
Optimal Values ◽  
Simulation Results ◽  
True Frequency

“Generalized” interpolation (called GIα here) of fast Fourier transform (FFT) spectra apodized by a family of sinα ( X) windows has previously been proposed. The GIα gives the highly accurate interpolated frequency by calculating the simple formula of frequency determination with the use of two squared ratios between three magnitudes nearest to the peak maximum on the apodized FFT spectrum. Although the value of window parameter α, limited to integer values, has been used for the GIα, we show in the present paper that the GIα with a real α value also gives an extremely good estimate of the true frequency from the sinα ( X)-apodized spectra. Thus, we intend to apply the GIα with the optimal values of α to FFT spectra apodized by any other window functions that are often used in Fourier spectroscopy. Simulation results show that the GIα is easier and more accurate than the KCe interpolation, which uses a family of interpolating functions [ KCe(ω) = ( aω2 + bω + c)e] proposed by Keefe and Comisarow. Finally, in the presence of noise we examine effects of damping and windowing on the frequency interpolation of FFT spectra. Because damping and windowing reduce the signal-to-noise ratio (SNR), we define anew the relative SNR by the ratio of the SNR of the apodized spectrum of a damped sinusoid to the SNR of the unapodized spectrum of an undamped sinusoid. Numerical calculation shows that the relative SNR varies, owing to damping rather than windowing. In fact, the observed frequency error roughly increases as the damping ratio increases for any window functions, as is expected from our previous investigation that the frequency error based upon the GIα is inversely proportional to the SNR. However, no obvious differences between the various window functions are observed in the presence of noise.

Digital Modulation Recognition in Different Environments

2014 ◽  
Vol 1049-1050 ◽  
pp. 2084-2087 ◽  
Author(s):  
Rong Li
Keyword(s):  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Automatic Recognition ◽  
Modulation Recognition ◽  
Signal To Noise ◽  
Digital Modulation ◽  
Multipath Interference ◽  
Modulation Signal ◽  
Simulation Results ◽  
Recognition Success

For the using of multi-modulation, the precondition of receiving and demodulating signal is to determine the type of the modulation, so automatic recognition of modulation signal has significant influence on the analysis of the signals. In this paper, digital modulation recognition is studied respectively in different environment of White Gaussian Noise (WGN), stationary interference and multipath interference. The simulation results show that the recognition success rate is the highest in stationary interference environment and the lowest in multipath interference environment with the same signal to noise ratio (SNR).

scholarly journals Superposition Coded Modulation Based Faster-Than-Nyquist Signaling

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Shuangyang Li ◽  
Baoming Bai ◽  
Jing Zhou ◽  
Qingli He ◽  
Qian Li
Keyword(s):  
Bit Error Rate ◽  
Spectral Efficiency ◽  
Detection Method ◽  
Signal To Noise Ratio ◽  
Coded Modulation ◽  
Signal To Noise ◽  
Data Rates ◽  
Orthogonal Signaling ◽  
Simulation Results ◽  
Constrained Capacity

A structure of faster-than-Nyquist (FTN) signaling combined with superposition coded modulation (SCM) is considered. The so-called FTN-SCM structure is able to achieve the constrained capacity of FTN signaling and only requires a low detection complexity. By deriving a new observation model suitable for FTN-SCM, we offer the power allocation based on a proper detection method. Simulation results show that, at any given spectral efficiency, the bit error rate (BER) curve of FTN-SCM lies clearly outside the minimum signal-to-noise ratio (SNR) boundary of orthogonal signaling with a larger alphabet. The achieved data rates are also close to the maximum data rates of the certain shaping pulse.

scholarly journals Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection

2021 ◽  
Vol 18 (5) ◽  
pp. 6771-6789
Author(s):  
Hongyan Xu ◽  
Keyword(s):  
Edge Detection ◽  
Digital Media ◽  
Copyright Protection ◽  
Detection Rate ◽  
Signal To Noise Ratio ◽  
Edge Computing ◽  
Absolute Difference ◽  
Watermark Image ◽  
Signal To Noise ◽  
Noise Ratio

<abstract> <p>With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.</p> </abstract>

scholarly journals Optimization of Direct Direction Finding Method with Two-Dimensional Correlative Processing of Spatial Signal

2018 ◽  
Vol 8 ◽  
pp. 46-53
Author(s):  
Vitaliy V. Tsyporenko ◽  
Valentyn G. Tsyporenko
Keyword(s):  
Main Parameter ◽  
Noise Immunity ◽  
Signal To Noise Ratio ◽  
Direction Finding ◽  
High Accuracy ◽  
Signal To Noise ◽  
High Noise ◽  
Spatial Shift ◽  
Simulation Results ◽  
Finding Method

In this article, the main parameter of the correlative-interferometric direction finding method with twodimensional correlative processing of spatial signal in the aperture of a linear antenna array (AA) is determined as the value of spatial shift within the AA aperture. The corresponding objective function is also formed. Analytical optimization of this parameter is presented and a comparative analysis of analytical calculations based on simulation results is conducted. In the simulation, a range of dependencies of the middle square deviation of estimation of direction on the value of the spatial shift for a signal-to-noise ratio of 0 dB, for minimum 3-sample and 4-sample Blackman-Harris windows of the spectral analysis, is received. The value of the middle square deviation of estimation of direction will be minimal and will equal 0.02 degrees using a minimum 3-sample Blackman-Harris window with the −67 dB level of side lobes. It offers high noise immunity and high accuracy of direction finding.

scholarly journals Image Noise Removal Method Based on Improved Nonlocal Mean Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Keya Huang ◽  
Hairong Zhu
Keyword(s):  
Signal To Noise Ratio ◽  
Median Filter ◽  
Visual Quality ◽  
Noise Removal ◽  
Interactive Systems ◽  
Image Processing Algorithm ◽  
Signal To Noise ◽  
Adaptive Median Filter ◽  
Mixed Noise ◽  
Filtering Effect

Aiming at the problem of unclear images acquired in interactive systems, an improved image processing algorithm for nonlocal mean denoising is proposed. This algorithm combines the adaptive median filter algorithm with the traditional nonlocal mean algorithm, first adjusts the image window adaptively, selects the corresponding pixel weight, and then denoises the image, which can have a good filtering effect on the mixed noise. The experimental results show that, compared with the traditional nonlocal mean algorithm, the algorithm proposed in this paper has better results in the visual quality and peak signal-to-noise ratio (PSNR) of complex noise images.

scholarly journals An Algorithm for Automatic Recogniton of Digital QAM Modulations

2019 ◽  
Vol 25 (3) ◽  
pp. 36-41
Author(s):  
Alexandru-Daniel Luţă ◽  
Paul Bechet
Keyword(s):  
Lower Order ◽  
Signal To Noise Ratio ◽  
Recognition Rate ◽  
Automatic Recognition ◽  
Signal To Noise ◽  
Small Influence ◽  
Qam Modulation ◽  
Digital Modulations ◽  
Simulation Results ◽  
Noise Ratio

Abstract This paper proposes a new Matlab-developed algorithm for automatic recognition of digital modulations using the constellation of states. Using this technique the automatic distinction between four digital modulation schemes (8-QAM, 16-QAM, 32-QAM and 64-QAM) was made. It has been seen that the efficiency of the algorithm is influenced by the type of modulation, the value of the signal-to-noise ratio and the number of samples. In the case of an AWGN noise channel the simulation results indicated that the value of SNR (signal-to-noise ratio) has a small influence on the recognition rate for lower-order QAM (8-QAM and 16-QAM). The length of the signal may change essentially the recognition rate of this algorithm especially for modulations with a high number of bits per symbol. Consequently, for the 64-QAM modulation in a case of 25dB signal-to-noise ratio the recognition rate is doubled if the sample rate is incresed from 5400 to 80640.

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