Effect of channel noise and dynamic synapse structure on latency dynamics in neural system

2018 ◽  
Author(s):  
Ali Calim ◽  
Mahmut Ozer ◽  
Muhammet Uzuntarla
Keyword(s):  
Neural System ◽  
Channel Noise ◽  
Dynamic Synapse

Predicting spatial activity patterns in a neural map from a probabilistic atlas of 3-D reconstructed neurons

1995 ◽  
Vol 53 ◽  
pp. 812-813
Author(s):  
G. Jacobs ◽  
F. Theunissen
Keyword(s):  
Activity Patterns ◽  
Three Dimensional ◽  
Sensory System ◽  
Neural System ◽  
Probabilistic Atlas ◽  
Uniform Sample ◽  
Dimensional Reconstruction ◽  
The Time Domain ◽  
And Function ◽  
Visualization Techniques

In order to understand how the algorithms underlying neural computation are implemented within any neural system, it is necessary to understand details of the anatomy, physiology and global organization of the neurons from which the system is constructed. Information is represented in neural systems by patterns of activity that vary in both their spatial extent and in the time domain. One of the great challenges to microscopists is to devise methods for imaging these patterns of activity and to correlate them with the underlying neuroanatomy and physiology. We have addressed this problem by using a combination of three dimensional reconstruction techniques, quantitative analysis and computer visualization techniques to build a probabilistic atlas of a neural map in an insect sensory system. The principal goal of this study was to derive a quantitative representation of the map, based on a uniform sample of afferents that was of sufficient size to allow statistically meaningful analyses of the relationships between structure and function.

Detection of Malicious Spatial-Domain Steganography over Noisy Channels Using Convolutional Neural Networks

2020 ◽  
Vol 2020 (4) ◽  
pp. 76-1-76-7
Author(s):  
Swaroop Shankar Prasad ◽  
Ofer Hadar ◽  
Ilia Polian
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Channel Noise ◽  
Detection Accuracy ◽  
Noisy Channel ◽  
Noisy Channels ◽  
Reliable Transmission ◽  
Reliable Detection ◽  
Natural Noise ◽  
Will Force

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.

scholarly journals Ischemic Stroke Prediction by Exploring Sleep Related Features

2021 ◽  
Vol 11 (5) ◽  
pp. 2083
Author(s):  
Jia Xie ◽  
Zhu Wang ◽  
Zhiwen Yu ◽  
Bin Guo ◽  
Xingshe Zhou
Keyword(s):  
Ischemic Stroke ◽  
Life Quality ◽  
Area Under The Curve ◽  
Prediction Method ◽  
Neural System ◽  
Human Beings ◽  
Filter Model ◽  
Fine Grained ◽  
Proposed Model ◽  
Precision Recall Curve

Ischemic stroke is one of the typical chronic diseases caused by the degeneration of the neural system, which usually leads to great damages to human beings and reduces life quality significantly. Thereby, it is crucial to extract useful predictors from physiological signals, and further diagnose or predict ischemic stroke when there are no apparent symptoms. Specifically, in this study, we put forward a novel prediction method by exploring sleep related features. First, to characterize the pattern of ischemic stroke accurately, we extract a set of effective features from several aspects, including clinical features, fine-grained sleep structure-related features and electroencephalogram-related features. Second, a two-step prediction model is designed, which combines commonly used classifiers and a data filter model together to optimize the prediction result. We evaluate the framework using a real polysomnogram dataset that contains 20 stroke patients and 159 healthy individuals. Experimental results demonstrate that the proposed model can predict stroke events effectively, and the Precision, Recall, Precision Recall Curve and Area Under the Curve are 63%, 85%, 0.773 and 0.919, respectively.

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

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.

scholarly journals Genetically magnetic control of neural system via TRPV4 activation with magnetic nanoparticles

Nano Today ◽  
2021 ◽  
Vol 39 ◽  
pp. 101187
Author(s):  
Songfang Wu ◽  
Hong Li ◽  
Dongqi Wang ◽  
Luming Zhao ◽  
Xin Qiao ◽  
...  
Keyword(s):  
Magnetic Nanoparticles ◽  
Neural System ◽  
Magnetic Control
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