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2016 2nd Workshop on Advanced Research and Technology in Industry Applications(WARTIA 2016)

作者： Qingchun Jiao Guangping Zhou Ning Li School of Automation & Electrical Engineering Zhejiang University of Science & Technology School of Information & Electronic Engineering Zhejiang University of Science & Technology Standardization Research Institute of Zhejiang Province

information classification and coding is the fundamental work of *** is an important way to solve difficult issues in information system construction such as non-unified information format,information sharing and exchange *** analyzing the information classification and coding research progress,based on the current developing of smart residing,an information sharing oriented smart residing information classification and coding system was proposed in this paper and the coding process was *** results of this study will help to promote the smart residing informatization,and improve the level of exchanging and sharing of smart residing information resources.

关键词： Smart residing information classification information coding

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Applications of dynamical systems with external perturbations for information encoding and hidden data transmission

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2005年第12期50卷 1358-1366页

作者： Loskutov, AY Rybalko, SD

A new method for information processing and hidden data transmission is proposed that uses stabilized orbits of the families of dynamical systems for encoding alphabetic characters, which are put in a biunique correspondence with the periods of such orbits. An allowable noise level in the communications channel and the degree of randomness of transmitted signals are analytically estimated. The examples of encoded letter sequences are presented.

关键词： information Processing DYNAMICAL SYSTEMS Hidden data data transmission Random Number Generators Noise levels perturbation information coding family

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Building partially understandable convolutional neural networks by differentiating class-related neural nodes

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NEUROCOMPUTING 2021年 452卷 169-181页

作者： Dai, Dawei Tang, Chengfu Wang, Guoyin Xia, Shuyin Chongqing Univ Posts & Telecommun Coll Comp Sci & Technol Chongqing Peoples R China Fudan Univ Dept Comp Sci & Technol Shanghai Peoples R China

In recent years, convolutional neural networks (CNNs) have been successfully applied in the field of image processing, and have been deployed to a variety of artificial intelligence systems. However, such neural models are still considered to be "black box" for most tasks. Two of fundamental issues underlying this problem are as follows: 1. What type of knowledge learned by a neural network in a task was not understandable and predictable? 2. The decision made by a neural model was generally not evaluable. Like neural coding in the brain, some neurons only participated in encoding a particular task. Inspired by this, in this paper, we propose a method to modify traditional CNN models into understandable CNNs, to clarify the information coding in high conv-layers of CNNs and further evaluate the decisions made by a neural model. In our understandable CNN models, each neural node (feature map) in a selected conv-layer was assigned to participate in encoding only one class in a classification task. Our models use the same training data as ordinary models without the need for additional annotations for supervision. We applied our method to the ResNet and DenseNet models. The experiments showed that new models can learn the information coding mode that we expected in an image-recognition task, and, using the preassigned coding mode, we can interpret why a neural model makes a right or wrong decision, which decisions are credible, and which are not. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Understandable neural network information coding CNN

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Fluorescence-enhanced Cs2Ag0.3-xNaxZn0.35In1-yCl6:yM double perovskites for multimodal optical anti-counterfeiting

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JOURNAL OF SOLID STATE CHEMISTRY 2024年 335卷

作者： Long, Gang Teng, Xiyue Qiao, Xiangkai Meng, Ziwei Zheng, Yalin Abdukayum, Abdukader Kashi Univ Coll Chem & Environm Sci Xinjiang Key Lab Novel Funct Mat Chem Kashgar 844000 Peoples R China

The excellent optical properties of lead-free halide double perovskites (LHDPs) Cs2AgInCl6 are of great importance in the field of anti-counterfeiting encryption. However, the fluorescence quantum yield of the existing Cs2AgInCl6-based materials is relatively low, and the fluorescence color is monochromatic, making it difficult to use in advanced multi-mode anti-counterfeiting applications. In this study, we synthesized Cs2Ag0.3-xNaxZn0.35In1-yCl6:yM (M = Cr/Bi) series LHDPs using an anti-solvent assisted co-precipitation method, improving the optical properties of Cs2AgInCl6-based materials by optimizing their composition. The fluorescence quantum yield of Zn-Na substituted Cr-doped Cs2Ag0.3-xNaxZn0.35In1-yCl6 LHDPs increased from 1.53 % to 82.57 % on the basis of Cs2AgInCl6. The Zn-Na substituted Bi-doped Cs2Ag0.3-xNaxZn0.35In1-yCl6 LHDPs exhibited dualwavelength fluorescence emission at 407 and 650 nm, and the relative intensity between the two emission wavelengths changed via a change in the Bi doping amount, resulting in a change in the material's luminescence color. The as-synthesized LHDPs could be applied to multi-mode anti-counterfeiting, optical coding information storage, and art decoration applications.

关键词： Lead-free halide double perovskite Fluorescence quantum yield Ratiometric emission Multi -mode anti-counterfeiting information coding

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Complex dynamics and autapse-modulated information patterns in memristive Wilson neurons

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NONLINEAR DYNAMICS 2022年第3期110卷 2793-2804页

作者： Njitacke, Zeric Tabekoueng Takembo, Clovis Ntahkie Koumetio, Bernard Nzoko Awrejcewicz, Jan Univ Buea Dept Elect & Elect Engn Coll Technol COT POB 63 Buea Cameroon Lodz Univ Technol Fac Mech Engn Dept Automat Biomech & Mechatron Lodz Poland Univ Dschang Res Unit Condensed Matter Dept Phys Fac SciElect & Signal Proc URMACETS POB 67 Dschang Cameroon

This paper introduces and investigates the dynamics of an improved Wilson neuron model with a memristive autapse. The study of the stability of the equilibrium points of the proposed model revealed that it can move from a rest state to a firing state through a Hopf bifurcation. Therefore, the improved model experiences self-excited dynamics. The study of the dynamics of the proposed model revealed neuronal behaviors such as quiescent, bursting, spiking, and hysteretic dynamics characterized by the coexistence of two and three firing patterns for the same set of parameters. In addition, the dynamics of modulated information patterns via the membrane potential related to potential information coding in a network of 500 neurons are presented and discussed. Planar impulse wave solutions of the generic model as initial conditions result in a localized unstable wave pattern under autaptic coupling and magnetic flux time delay. High memristive autaptic coupling and magnetic flux time delay have antagonistic effects on the spatiotemporal patterns. Our results suggest that high autaptic coupling could be a possible route to chaotic and chimera-like behaviors in the network, while high magnetic flux time delay could be an efficient bifurcation parameter in controlling the chaotic and chimera-like behaviors. Finally, a microcontroller implementation of the introduced memristive Wilson neuron has been addressed based on the 32-bit STM32F407ZE development board. Results obtained from the experimental investigations of the model agreed with the numerical ones based on the physically captured phase trajectories and time-domain waveforms.

关键词： Wilson neuron Memristive autapse Coexisting firing patterns Network of neurons information coding MCU-based hardware platform

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Microfluidic spinning of editable polychromatic fibers

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JOURNAL OF COLLOID AND INTERFACE SCIENCE 2020年 558卷 115-122页

作者： Zhang, Wei Hou, Chengyi Li, Yaogang Zhang, Qinghong Wang, Hongzhi Donghua Univ Coll Mat Sci & Engn State Key Lab Modificat Chem Fibers & Polymer Mat Int Joint Lab Adv Fiber & Low Dimens Mat Shanghai 201600 Peoples R China Donghua Univ Coll Mat Sci & Engn Engn Res Ctr Adv Glasses Mfg Technol Shanghai 201600 Peoples R China

Chromatic fibers that change color in response to external stimuli are expected to be widely used in various applications such as anti-counterfeiting, military camouflage, and wearable displays. Advanced chromatic fibers with polychromatic and editable color properties behavior are strongly desired for practical applications but have not yet been realized using existing spinning technologies. Here, we present the low-cost, continuous microfluidic spinning of editable polychromatic polylactide (PLA) fibers. The structure and performance of the polychromatic PLA fibers were precisely controlled by adjusting the parameters used in microfluidic spinning. The structure of the as-spun products evolved through three different stages based on the editable encapsulation of functional materials into the PLA matrix. Fibers with versatile performance were achieved. A beaded polychromatic PLA fiber showed the possibility to delivery coded information through its editable chromatic behavior. A core-shell polychromatic PLA fiber showed good mechanical properties and knittability, which make it promising to fabricate smart color-changing textiles. (C) 2019 Published by Elsevier Inc.

关键词： Microfluidic spinning Editable polychromatism information coding Thermochromic PLA fibers

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A New Work Mechanism on Neuronal Activity

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INTERNATIONAL JOURNAL OF NEURAL SYSTEMS 2015年第3期25卷 1450037-1450037页

作者： Wang, Rubin Tsuda, Ichiro Zhang, Zhikang E China Univ Sci & Technol Sch Sci Inst Cognit Neurodynam Shanghai 200237 Peoples R China E China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China Hokkaido Univ Res Inst Elect Sci Kita Ku Sapporo Hokkaido 0010012 Japan

By re-examining the neuronal activity energy model, we show the inadequacies in the current understanding of the energy consumption associated with neuron activity. Specifically, we show computationally that a neuron first absorbs and then consumes energy during firing action potential, and this result cannot be produced from any current neuron models or biological neural networks. Based on this finding, we provide an explanation for the observation that when neurons are excited in the brain, blood flow increases significantly while the incremental oxygen consumption is very small. We can also explain why external stimulation and perception emergence are synchronized. We also show that negative energy presence in neurons at the sub-threshold state is an essential reason that leads to blood flow incremental response time in the brain rather than neural excitation to delay.

关键词： Action potential information coding neuronal energy coding negative neuronal energy neural energy field

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Efficient and secure communication scheme for OFDM system based on physical layer non-reconciled keys

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IET COMMUNICATIONS 2022年第6期16卷 659-671页

作者： Song, Xuanyan Jin, Liang Huang, Kaizhi Xiao, Shuaifang Sun, Xiaoli Zhao, Jianlei PLA Strateg Support Force Informat Engn Univ Zhengzhou 450001 Peoples R China Purple Mt Labs Networking Commun & Secur Nanjing Peoples R China

The secure communication scheme based on physical layer non-reconciled keys receives extensive attention due to its high encryption rate. However, the mismatched secret bit sequences between the two users leads to higher BER and lower coding efficiency for this type of scheme. To solve this problem, this paper proposes an efficient and secure communication scheme for OFDM system with non-reconciled keys. Initially, an adaptive coding method is designed to encode information blocks with different code rates to improve the overall efficiency. Then, on this basis, a sorting xor encryption algorithm is designed to reduce the bit error rate by sorting the channel estimation value and mapping them to corresponding sub-channels. Theoretical analysis and simulation results indicate that this scheme can effectively reduce the bit error rate and improve the efficiency of information coding compared to the existing method.

关键词： information coding BER cryptography adaptive codes channel estimation adaptive coding method sorting xor encryption algorithm high encryption rate OFDM system telecommunication security channel estimation val error statistics information blocks physical layer nonreconciled keys bit error rate lower coding efficiency OFDM modulation mismatched secret bit sequences radio networks different code rates secure communication scheme

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Axonal geometry as a tool for modulating firing patterns

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APPLIED MATHEMATICAL MODELLING 2016年第4期40卷 3175-3184页

作者： Ofer, Netanel Shefi, Orit Bar Ilan Univ Fac Engn IL-5290002 Ramat Gan Israel Bar Ilan Univ Bar Ilan Inst Nanotechnol & Adv Mat IL-5290002 Ramat Gan Israel

Neurons generate diverse patterns of activity for various functions. Revealing factors which determine neuronal firing patterns is fundamental to a better understanding of brain activity and coding. Traditionally, the space clamp model has been used to investigate neuronal electrical activity. In this paper, we study the Hodgkin-Huxley cable model, taking into consideration axonal geometry. We examine the influence of morphology on neuronal activity, exploring neuronal response to constant current stimuli injected into one end of fiber-like axons of different lengths and radii. We demonstrate novel patterns of firing, including a finite number of spikes and series followed by failures, and under some specific current stimulus regimes, we also detect irregular behaviors. Our results illustrate various means in which the pattern of activity may be regulated by axonal structure, suggesting this mechanism is instrumental in information coding of physiological, as well as deforming pathological conditions. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Cable model Hodgkin-Huxley model information coding Neuronal activity Neuronal morphology Non-linear dynamics

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information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system

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BIOLOGICAL CYBERNETICS 2020年第3期114卷 403-418页

作者： Bostner, Ziga Knoll, Gregory Lindner, Benjamin Humboldt Univ Phys Dept Newtonstr 15 D-12489 Berlin Germany Bernstein Ctr Computat Neurosci Berlin Philippstr 13Haus 2 D-10115 Berlin Germany

information about time-dependent sensory stimuli is encoded in the activity of neural populations;distinct aspects of the stimulus are read out by different types of neurons: while overall information is perceived by integrator cells, so-calledcoincidence detectorcells are driven mainly by the synchronous activity in the population that encodes predominantly high-frequency content of the input signal (high-pass information filtering). Previously, an analytically accessible statistic called the partial synchronous output was introduced as a proxy for the coincidence detector cell's output in order to approximate its information transmission. In the first part of the current paper, we compare the information filtering properties (specifically, the coherence function) of this proxy to those of a simple coincidence detector neuron. We show that the latter's coherence function can indeed be well-approximated by the partial synchronous output with a time scale and threshold criterion that are related approximately linearly to the membrane time constant and firing threshold of the coincidence detector cell. In the second part of the paper, we propose an alternative theory for the spectral measures (including the coherence) of the coincidence detector cell that combines linear-response theory for shot-noise driven integrate-and-fire neurons with a novel perturbation ansatz for the spectra of spike-trains driven by colored noise. We demonstrate how the variability of the synaptic weights for connections from the population to the coincidence detector can shape the information transmission of the entire two-stage system.

关键词： information coding Synchronization Coincidence detection Neural computation

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