Networked fusion estimation with multiple uncertainties and time-correlated channel noise

Image steganography can have legitimate uses, for example, augmenting an image with a watermark for copyright reasons, but can also be utilized for malicious purposes. We investigate the detection of malicious steganography using neural networkbased classification when images are transmitted through a noisy channel. Noise makes detection harder because the classifier must not only detect perturbations in the image but also decide whether they are due to the malicious steganographic modifications or due to natural noise. Our results show that reliable detection is possible even for state-of-the-art steganographic algorithms that insert stego bits not affecting an image’s visual quality. The detection accuracy is high (above 85%) if the payload, or the amount of the steganographic content in an image, exceeds a certain threshold. At the same time, noise critically affects the steganographic information being transmitted, both through desynchronization (destruction of information which bits of the image contain steganographic information) and by flipping these bits themselves. This will force the adversary to use a redundant encoding with a substantial number of error-correction bits for reliable transmission, making detection feasible even for small payloads.

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Multiclass Classification of Modulation Formats in the presence of Rayleigh and Rician Channel Noise using Deep Learning Methods

2020 3rd International Conference on Information and Communications Technology (ICOIACT) ◽

10.1109/icoiact50329.2020.9332035 ◽

2020 ◽

Author(s):

Rahim Khan ◽

Yang Qiang ◽

Ahsan Bin Tufail ◽

Alam Noor

Keyword(s):

Deep Learning ◽

Multiclass Classification ◽

Channel Noise ◽

Learning Methods ◽

Modulation Formats ◽

Rician Channel

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Impact of Pointing Error on the BER Performance of an OFDM Optical Wireless Communication Link over Turbulent Condition

Journal of Optical Communications ◽

10.1515/joc-2020-0021 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Bobby Barua ◽

S. P. Majumder

Keyword(s):

Noise Analysis ◽

Data Rate ◽

Channel Noise ◽

Communication Link ◽

Optical Wireless ◽

Power Penalty ◽

Major Power ◽

Pointing Error ◽

Turbulent Condition ◽

Ber Performance

AbstractAn analytical approach is developed in this paper to evaluate the bit error rate (BER) performance of an optical wireless (OW) communication system with multiplexing of the RF orthogonal frequency division (OFDM) over turbulent condition taking into account the effect of pointing error. The received signal is detected through direct detection receiver followed by RF synchronous demodulation including the effect of OW channel and different form of noises such as receiver thermal noise, background channel noise and photo detector shot noise. Analysis is developed for an OFDM system over the OW channel, taking into account the effect of pointing error between the transmitter and the receiver in turbulent condition and the analysis reveals that the OFDM OW system is less affected by pointing error with deference to the major power penalty at BER performance. For instance, power penalty at BER 10−9 is found to be 3 dB for 256 OFDM subcarriers with 9 millidegree displacement angle at a data rate of 10 Gbps under turbulent condition. It is found that the system is more influenced by the atmospheric turbulence at a higher data rate.

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High Resolution, High Contrast Beamformer Using Minimum Variance and Plane Wave Nonlinear Compounding with Low Complexity

Sensors ◽

10.3390/s21020394 ◽

2021 ◽

Vol 21 (2) ◽

pp. 394

Author(s):

Xin Yan ◽

Yanxing Qi ◽

Yinmeng Wang ◽

Yuanyuan Wang

Keyword(s):

Plane Wave ◽

Dimensional Space ◽

Contrast Ratio ◽

Low Complexity ◽

Minimum Variance ◽

Frame Rate ◽

Channel Noise ◽

Length Estimation ◽

Lower Dimensional Space

The plane wave compounding (PWC) is a promising modality to improve the imaging quality and maintain the high frame rate for ultrafast ultrasound imaging. In this paper, a novel beamforming method is proposed to achieve higher resolution and contrast with low complexity. A minimum variance (MV) weight calculated by the partial generalized sidelobe canceler is adopted to beamform the receiving array signals. The dimension reduction technique is introduced to project the data into lower dimensional space, which also contributes to a large subarray length. Estimation of multi-wave receiving covariance matrix is performed and then utilized to determine only one weight. Afterwards, a fast second-order reformulation of the delay multiply and sum (DMAS) is developed as nonlinear compounding to composite the beamforming output of multiple transmissions. Simulations, phantom, in vivo, and robustness experiments were carried out to evaluate the performance of the proposed method. Compared with the delay and sum (DAS) beamformer, the proposed method achieved 86.3% narrower main lobe width and 112% higher contrast ratio in simulations. The robustness to the channel noise of the proposed method is effectively enhanced at the same time. Furthermore, it maintains a linear computational complexity, which means that it has the potential to be implemented for real-time response.

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An Inexact Inventory Theory-Based Water Resources Distribution Model for Yuecheng Reservoir, China

Mathematical Problems in Engineering ◽

10.1155/2020/6273513 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Meiqin Suo ◽

Fuhui Du ◽

Yongping Li ◽

Tengteng Kong ◽

Jing Zhang

Keyword(s):

Water Resources ◽

Water Distribution ◽

Water Diversion ◽

Distribution Model ◽

Inventory Theory ◽

Resources Management ◽

Resources Distribution ◽

Multiple Uncertainties ◽

System Benefit ◽

Decision Alternatives

In this study, an inexact inventory theory-based water resources distribution (IIWRD) method is advanced and applied for solving the problem of water resources distribution from Yuecheng Reservoir to agricultural activities, in the Zhanghe River Basin, China. In the IIWRD model, the techniques of inventory model, inexact two-stage stochastic programming, and interval-fuzzy mathematics programming are integrated. The water diversion problem of Yuecheng Reservoir is handled under multiple uncertainties. Decision alternatives for water resources allocation under different inflow levels with a maximized system benefit and satisfaction degree are provided for water resources management in Yuecheng Reservoir. The results show that the IIWRD model can afford an effective scheme for solving water distribution problems and facilitate specific water diversion of a reservoir for managers under multiple uncertainties and a series of policy scenarios.

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