基于神经网络的探地雷达数据去噪

探地雷达数据在实际工程检测过程中常被各种随机噪声污染,而数据中的噪声会降低数据的信噪比和分辨率,进而给后续的反演和解释等工作带来不利影响。对此,本文开展了基于神经网络的探地雷达数据去噪研究。首先,建立1个多层神经网络,向无噪声数据加入高斯白噪声破坏数据。然后,将破坏后的数据和其对应的噪声的patch建立训练数据,通过反向传播算法更新模型各层神经元权重,使得模型训练损失值最小。最后,将两个合成数据和实测雷达数据输入到已训练好的模型,用其训练得到噪声特性权重计算模型输出。通过与曲波法的数值模拟试验结果对比验证了本文方法的有效性和鲁棒性,且本文方法对结构复杂、幅值较弱区域的噪声压制更彻底,有效信号展现得更清晰。

一种差分进化BM3D硬阈值参数的遥感影像去噪方法

针对遥感影像高斯白噪声去噪的问题,本文首先利用差分进化(DE)优化三维块匹配(BM3D)中的硬阈值变换参数(参数包括块距离阈值和三维变换域硬阈值参数);然后使用优化的BM3D算法消除影像中高斯白噪声,以峰值信噪比(PSNR)、结构相似度(SSIM)和边缘保留指数(EPI)作为评价指标。试验结果表明,在噪声密度不同情况下,融合算法的PSNR、SSIM和EPI均有所提升,尤其EPI相较于BM3D算法提高约2%。整体上,融合算法的遥感影像高斯白噪声的去噪效果优于单一BM3D算法。

WNNM参数模型及迭代判断机制优化的遥感影像去噪

针对加权核范数最小化(weighted nuclear norm minimization,WNNM)算法经验参数多、无法适应遥感影像复杂降噪环境问题,提出利用遗传算法(genetic algorithm,GA)优化WNNM算法中的参数模型(非局部补丁搜索窗口、迭代步数、迭代变换参数)。首先,通过GA对WNNM参数模型中参数进行寻优;然后,在算法迭代计算中加入判断机制,当迭代为最优解之后跳出迭代循环;最后,利用优化后WNNM算法消除影像中高斯白噪声。通过灰度图像仿真实验和Landsat 8、GF-1遥感影像实验,以峰值信噪比(peak signal-to-noise ratio,PSNR)、结构相似度(structural similarity ratio,SSIM)作为评价指标,对该算法与其他算法处理结果进行对比分析。实验结果表明,在噪声密度不同的情况下,该算法的PSNR、SSIM均有所提升。总体上,该算法的遥感影像高斯白噪声的去噪效果优于其他经典去噪算法。

双边滤波在探地雷达数据去噪处理中的应用

在探地雷达数据的采集过程中,受外界因素影响会不可避免地混入噪声,严重干扰有效回波的识别与解译。为此,利用双边滤波算法进行探地雷达数据的去噪处理,通过在探地雷达正演记录加入高斯白噪声来模拟实测的探地雷达记录,利用双边滤波器对含噪声的合成记录进行滤波处理,结果表明双边滤波算法能除去大部分高斯噪声,突出有效回波信息,峰值信噪比(PSNR)由初始的15.8451增加到22.1477。进一步将双边滤波器用于实测记录的滤波,从滤波结果来看,噪声除去效果较好,表明双边滤波器能有效应用于探地雷达数据的去噪处理。

Edge enhancement of gravity anomalies and gravity gradient tensors using an improved small sub-domain filtering method

In order to enhance geological body boundary visual effects in images and improve interpretation accuracy using gravity and magnetic field data, we propose an improved small sub-domain filtering method to enhance gravity anomalies and gravity gradient tensors. We discuss the effect of Gaussian white noise on the improved small sub-domain filtering method, as well as analyze the effect of window size on geological body edge recognition at different extension directions. Model experiments show that the improved small sub-domain filtering method is less affected by noise, filter window size, and geological body edge direction so it can more accurately depict geological body edges than the conventional small sub-domain filtering method. It also shows that deeply buried body edges can be well delineated through increasing the filter window size. In application, the enhanced gravity anomalies and calculated gravity gradient tensors of the Hulin basin show that the improved small sub-domain filtering can recognize more horizontal fault locations than the conventional method.

Aperiodic stochastic resonance in Schmitt trigger

By the use of cross-correlation measures, the response of a symmetric Schmitt trigger (ST) driven by a random binary signal and white Gaussian noise is investigated. The results show that the information transmission can be enhanced when a certain amount of noise is presented, i.e., aperiodic stochastic resonance (ASR). Then, the influence of signal amplitude and the ST threshold on ASR is examined, the applicability of the ST in reducing the noise level of random signal transmission and improving the quality of output signal via ASR effect is illustrated. This research is of great interest in the field of digital communications.

Anti-Jamming Performance of Fountain Coded Differential Frequency Hopping Systems in AWGN

Based on the anti-jamming performance of differential frequency hopping （DFH） systems in Additive White Gaussian Noise （AWGN） channel, Fountain code is introduced to the DFH systems as the outer error correcting code in this paper to investigate the improvements against partial-band jamming over AWGN channel. The performance of Fountain coded DFH is theoretically analyzed and numerically simulated. The total frequency of hopping in the simulation is 16, and results show that, on one hand, when exact jamming state information （JSI） is available, and the number of jamming frequency is n= 16, the bit error rate （BER） of 10~3 is achieved with the signal to interference ratio （SIR） approximately 7.5 dB over AWGN channel, and the performance improves about 1-1.5dB compared with the no-coded system. When the number of jamming frequency is n=2, the performance increases 15-17dB. On the other hand, when JSI is unavailable, a joint JSI estimation and decoding algorithm is proposed. The BER of 10 3 is achieved with jamming-frequency n 16, SIR=8dB and signal noise ratio （SNR） 10dB over AWGN channel. It＇s proved that this algorithm provides robust anti-jamming pertbrmance even without JSI. The anti-jamming performance of Fountain coded DFH systems is obviously superior to no-coded DFH systems.

Removal of noises from electromagnetic radiation of coal or rock with EEMD-adaptive morphological filter

The electromagnetic radiation （EMR） signal collected by monitoring system during coal or rock dynamic disaster may be interferred easily by electromagnetic noises in mines. The noises have a direct influence on the recognition and analysis of the EMR signal features during the disaster. With the aim of removing these noises, an ensemble empirical mode decomposition （EEMD） adaptive morphological filter was proposed. From the result of the simulation and the experiment, it is shown that the method can restrain the random noise and white Gaussian noise mixed with EMR signal effectively. The filter is highly useful for improving the robustness of the coal or rock dynamic disaster monitoring system.

Frequency Offset Compensation for Satellite Communication System with CE-OFDM

Constant envelope orthogonal frequency division multiplexing(CE-OFDM) is a waveform that can achieve 0d B peak-to-average power ratio and avoid the signal distortion caused by the nonlinear power amplifi er. However, the carrier frequency offset(CFO) in CE-OFDM systems can cause errors at phase unwrapper module. In this paper, a CFO estimation scheme is proposed for CEOFDM in satellite communication system. As the null subcarrier is inherent in the conjugate symmetric symbol structure at the transmitter, the proposed scheme uses the null subcarrier as prior information to estimate the CFO at the receiver. The ideal estimation range of normalized CFO is obtained by mathematical analysis. Simulation results show that the proposed scheme can estimate the CFO accurately under additive white Gaussian noise(AWGN) channel and multipath fading channel, especially for moderate and high signal-to-noise ratio(SNR).

Joint Spectrum Sensing Based on Variance and Correlation Analysis

In this paper, a novel detection criterion is proposed to decide whether primary user(PU) exists based on joint analysis of the variance and correlation for observation signal,considering a correlation within the observed signal. Simultaneously, the corresponding detection thresholds are also designed. Simulation experiments verify the proposed method suits for the observation signal in Additive White Gaussian Noise(AWGN), Rayleigh,Rician channel and the detection performance is improved greatly.

Noise-Induced Transition in a Voltage-Controlled Oscillator Neuron Model

In the presence of Gaussian white noise,we study the properties of voltage-controlled oscillator neuronmodel and discuss the effects of the additive and multiplicative noise.It is found that the additive noise can accelerate andcounterwork the firing of neuron,which depends on the value of central frequency of neuron itself,while multiplicativenoise can induce the continuous change or mutation of membrane potential.

Steady State Properties of One-Dimensional Non-uniform Granular Gases Subjected to Gaussian White Noise Driving

We present a model of non-uniform granular gases in one-dimensional case, whose granularity distribution has the fractal characteristic. We have studied the nonequilibrium properties of the system by means of Monte Carlo method. When the typical relaxation time T of the Brownian process is greater than the mean collision time To, the energy evolution of the system exponentially decays, with a tendency to achieve a stable asymptotic value, and the system finally reaches a nonequilibrium steady state in which the velocity distribution strongly deviates from the Gaussian one. Three other aspects have also been studied for the steady state： the visualized change of the particle density, the entropy of the system and the correlations in the velocity of particles. And the results of simulations indicate that the system has strong spatial clustering; Furthermore, the influence of the inelasticity and inhomogeneity on dynamic behaviors have also been extensively investigated, especially the dependence of the entropy and the correlations in the velocity of particles on the restitute coefficient e and the fractal dimension D.

Spiral Wave in Small-World Networks of Hodgkin-Huxley Neurons

The effect of small-world connection and noise on of Hodgkin-Huxley neurons are investigated in detail. Some the formation and transition of spiral wave in the networks interesting results are found in our numerical studies, i） The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii） A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise, iii） Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv） Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Ganssian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave.

Resonant Activation Induced by Four-Value Noise

The phenomenon of the resonant activation （RA） of a particle over a fluctuating potential barrier with a four-value noise is investigated. It is shown that the mean first passage time （MFPT） displays six minima as the function of the transition rates γ1, γ2, γ3, γ4, γ5, and 76 of the four-value noise, respectively. In addition, the effect of other parameters of the system, such as the noise strength D of the additive Gaussian white noise and the parameter value a, b, c, and d of the four-value noise, on the RAs is also investigated.

Frame Detection Based on Cyclic Autocorrelation and Constant False Alarm Rate in Burst Communication Systems

Frame detection is important in burst communication systems for its contribu- tions in frame synchronization. It locates the information bits in the received data stream at receivers. To realize frame detection in the presence of additive white Gaussian noise （AWGN） and frequency offset, a constant false alarm rate （CFAR） detector is proposed through exploitation of cyclic autocorrelation feature implied in the preamble. The frame detection can be achieved prior to bit timing recovery. The threshold setting is independent of the signal level and noise level by utilizing CFAR method. Mathematical expressions is derived in AWGN channel by considering the probability of false alarm and probability of detection, separately. Given the probability of false alarm, the mathematical relationship between the frame detection performance and EJNo of received signals is established. Ex- perimental results are also presented in accor- dance with analysis.

Global Pressure of One-Dimensional Polydisperse Granular Gases Driven by Gaussian White Noise

We study the global pressure of a one-dimensional polydisperse granular gases system for the first time, in which the size distribution of particles has the fractal characteristic and the inhomogeneity is described by a fractal dimension D. The particles are driven by Gaussian white noise and subject to inelastic mutual collisions. We define the global pressure P of the system as the impulse transferred across a surface in a unit of time, which has two contributions, one from the translational motion of particles and the other from the collisions. Explicit expression for the global pressure in the steady state is derived. By molecular dynamics simulations, we investigate how the inelasticity of collisions and the inhomogeneity of the particles influence the global pressure. The simulation results indicate that the restitution coefficient e and the fractal dimension D have significant effect on the pressure.

Effects of Perfectly Correlated and Anti-Correlated Noise in a Logistic Growth Model

The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to anedyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in cause tumor cell extinction. In the perfectly anti-correlated tumor cell population exhibit two extrema. both cases, the increase of the multiplicative noise intensity case, the stationary probability distribution as a function of

Design of bilayer lengthened LDPC codes over expanded graph for relay channels

This paper presents a low complexity optimized algorithm for design of bilayer lengthened LDPC(BL-LDPC) code for decode-and-forward relay system.The design is performed over the expanded graph of the BL-LDPC code,which consists of the original bilayer graph and the extra added relaygenerated parity check bits.To build up our proposed optimized algorithm,we present a modified Gaussian approximation algorithm for the expanded structure of the BL-LDPC code.Then using the proposed optimized algorithm,we find the optimum overall expanded graph of the BL-LDPC code.Simulation results show that the BL-LDPC codes obtained by our proposed optimized algorithm have excellent bit-error-rate performances and small gaps between the convergence thresholds and the theoretical limits when transmitted over the additive white Gaussian noise channels.

A NEW LIKELIHOOD-BASED MODULATION CLASSIFICATION ALGORITHM USING MCMC

In this paper,a new likelihood-based method for classifying phase-amplitude-modulated signals in Additive White Gaussian Noise (AWGN) is proposed.The method introduces a new Markov Chain Monte Carlo (MCMC) algorithm,called the Adaptive Metropolis (AM) algorithm,to directly generate the samples of the target posterior distribution and implement the multidimensional integrals of likelihood function.Modulation classification is achieved along with joint estimation of unknown parameters by running an ergodic Markov Chain.Simulation results show that the proposed method has the advantages of high accuracy and robustness to phase and frequency offset.

Performance of Spread Spectrum Watermarking in Autoregressive Host Model Under Additive White Gaussian Noise Channel

A large class of multimedia and biomedical signals can be modeled as Autotegessive （AR） random processes. Pefformance of watermarking embedding algorithms utilizing this host model is still left unexplored. The authors investigate the decoding perform-nance of Spread Spectrum （SS） embedding algorithm in the standard Additive White Gaussian Noise （AWGN） channel with the host signal being modeled as AR process. The SS embedding algorithm also use linear interference cancelation in the subspace spanned by watermark pattern. They study the influence of design parameters on the decoding performance. The analytic result is verified by Monte Carlo simulation on synthesized AR process. The result may be helpful to design watermarking system for speech, biomedical and image signals.