Causal nets or what is a deterministic computation?

The network approach to computation is more direct and physical than the one based on some specific computing devices (like Turing machines). However, the size of a usual—e.g., Boolean—network does not reflect the complexity of computing the corresponding function, since a small network may be very hard to find even if it exists. A history of the work of a particular computing device can be described as a network satisfying some restrictions. The size of this network reflects the complexity of the problem, but the restrictions are usually somewhat arbitrary and even awkward. Causal nets are restricted only by determinism (causality) and locality of interaction. Their geometrical characteristics do reflect computational complexities. And various imaginary computer devices are easy to express in their terms. The elementarily of this concept may help bringing geometrical and algebraic (and maybe even physical) methods into the theory of computations. This hope is supported by the group-theoretical criterion given in this paper for computability from symmetrical initial configurations.Part of this work was done while this author was visiting Johann Wolfgang Goethe University, Frankfurt am Main in 1978 and Stanford University in 1979.The research of this author was partially supported by NSF grants MCS 77-19754 and MCS-8104211.     

控制器局域网络总线在阵列天线中的应用

为控制数万单元的阵列天线,基于控制器局域网络（CAN）总线设计了一套多级通信系统。分析了CAN总线的拓扑结构,根据每路CAN的带负载能力设计了多级CAN总线通信网络的基本结构;基于Nios II软核处理器设计了CAN总线通信节点硬件电路;最后根据阵列天线控制功能的要求,基于CAN2.0B协议设计了应用层通信协议和应用程序。阵列天线波束扫描实验表明,通信系统满足500 kbps以上传输速率的要求,通信时间抖动小于1 ms,当阵列天线辐射峰值功率达到GW量级时仍可以有效控制天线系统。     

Analysis of Transmission Performance in SUPERPONs

In this work we study how optical amplifiers can deeply improve the performance of the passive optical networks (PONs), permitting a large number of optical network units (ONUs), transmitting at high bit rate. These high-capacity networks are called SUPERPONs, and we show how to achieve a network with 8,192 ONUs with a transmission in the downstream direction up to 10 Gbit/s.     

Analysis of Transmission Performance in SUPERPONs

In this work we study how optical amplifiers can deeply improve the performance of the passive optical networks (PONs), permitting a large number of optical network units (ONUs), transmitting at high bit rate. These high-capacity networks are called SUPERPONs, and we show how to achieve a network with 8,192 ONUs with a transmission in the downstream direction up to 10 Gbit/s.     

Shuttle-run synchronization in mobile ad hoc networks

In this work, we study the collective dynamics of phase oscillators in a mobile ad hoc network whose topology changes dynamically. As the network size or the communication radius of individual oscillators increases, the topology of the ad hoc network first undergoes percolation, forming a giant cluster, and then gradually achieves global connectivity. It is shown that oscillator mobility generally enhances the coherence in such networks. Interestingly, we find a new type of phase synchronization/clustering, in which the phases of the oscillators are distributed in a certain narrow range, while the instantaneous frequencies change signs frequently, leading to shuttle-run-like motion of the oscillators in phase space. We conduct a theoretical analysis to explain the mechanism of this synchronization and obtain the critical transition point.     

Nonlinear signal transduction network with multistate

Signal transduction is an important and basic mechanism to cell life activities. The stochastic state transition of receptor induces the release of signaling molecular, which triggers the state transition of other receptors. It constructs a nonlinear sigaling network, and leads to robust switchlike properties which are critical to biological function. Network architectures and state transitions of receptor affect the performance of this biological network. In this work, we perform a study of nonlinear signaling on biological polymorphic network by analyzing network dynamics of the Ca²⁺-induced Ca²⁺ release (CICR) mechanism, where fast and slow processes are involved and the receptor has four conformational states. Three types of networks, Erdös-Rényi (ER) network, Watts-Strogatz (WS) network, and BaraBási-Albert (BA) network, are considered with different parameters. The dynamics of the biological networks exhibit different patterns at different time scales. At short time scale, the second open state is essential to reproduce the quasi-bistable regime, which emerges at a critical strength of connection for all three states involved in the fast processes and disappears at another critical point. The pattern at short time scale is not sensitive to the network architecture. At long time scale, only monostable regime is observed, and difference of network architectures affects the results more seriously. Our finding identifies features of nonlinear signaling networks with multistate that may underlie their biological function.     

Chemomechanical Coupling of Molecular Motors: Thermodynamics, Network Representations, and Balance Conditions

Molecular motors are considered that convert the chemical energy released from the hydrolysis of adenosine triphosphate (ATP) into mechanical work. Such a motor represents a small system that is coupled to a heat reservoir, a work reservoir, and particle reservoirs for ATP, adenosine diphosphate (ADP), and inorganic phosphate (P). The discrete state space of the motor is defined in terms of the chemical composition of its catalytic domains. Each motor state represents an ensemble of molecular conformations that are thermally equilibrated. The motor states together with the possible transitions between neighboring states define a network representation of the motor. The motor dynamics is described by a continuous-time Markov process (or master equation) on this network. The consistency between thermodynamics and network dynamics implies (i) local and nonlocal balance conditions for the transition rates of the motor and (ii) an underlying landscape of internal energies for the motor states. The local balance conditions can be interpreted in terms of constrained equilibria between neighboring motor states; the nonlocal balance conditions pinpoint chemical and/or mechanical nonequilibrium.     

Synchronization investigation of the network group constituted by the nearest neighbor networks under inner and outer synchronous couplings

A new synchronization technique of inner and outer couplings is proposed in this work to investigate the synchronization of network group. Some Haken–Lorenz lasers with chaos behaviors are taken as the nodes to construct a few nearest neighbor complex networks and those sub-networks are also connected to form a network group. The effective node controllers are designed based on Lyapunov function and the complete synchronization among the sub-networks is realized perfectly under inner and outer couplings. The work is of potential applications in the cooperation output of lasers and the communication network.     

Impact of Ta/Ti electrodes on linearities of TaO_x-based resistive random-access memories for neuromorphic computing

In this work, by incorporating different electrodes(Ta/Ti) onto TaOxdielectric layer, we studied both the conductance reading and conductance updating(long term potentiation and depression) linearities in the two RRAM devices. Owing to the composition modulation(CM) mechanism, the Ta-electrode device shows better conductance reading and updating linearities. The RRAM device linearities directly influence the performance of the neural network when the devices are used as synapses. System evaluation of a two-layer neural network considering the conductance reading and updating linearity factors further confirm that both the training and inference accuracies of Ta electrode device are better than those of the Ti electrode one. We believe that this work could serve as a powerful reference for engineering synaptic devices with good linearity for neuromorphic computing applications.     

A Hopfield neural network with multiple attractors and its FPGA design

Neural network is important for a wide range of applications. Especially, a small neural network can display various complex behaviors. In this work, the investigations of a Hopfield neural network and its field programmable gate array (FPGA) implementation have been reported. The considered Hopfield neural network is simple because it includes only three neurons. It is interesting that we observed chaos and numerous coexisting attractors in such a network. In addition, the network has been implemented via an FPGA platform to verify its feasibility.     

ECG Signal Classification Using Deep Learning Techniques Based on the PTB-XL Dataset

The analysis and processing of ECG signals are a key approach in the diagnosis of cardiovascular diseases. The main field of work in this area is classification, which is increasingly supported by machine learning-based algorithms. In this work, a deep neural network was developed for the automatic classification of primary ECG signals. The research was carried out on the data contained in a PTB-XL database. Three neural network architectures were proposed: the first based on the convolutional network, the second on SincNet, and the third on the convolutional network, but with additional entropy-based features. The dataset was divided into training, validation, and test sets in proportions of 70%, 15%, and 15%, respectively. The studies were conducted for 2, 5, and 20 classes of disease entities. The convolutional network with entropy features obtained the best classification result. The convolutional network without entropy-based features obtained a slightly less successful result, but had the highest computational efficiency, due to the significantly lower number of neurons.     

Brain-like synaptic memristor based on lithium-doped silicate for neuromorphic computing

Artificial synapse is one of the potential electronics for constructing neural network hardware. In this work, Pt/LiSiO_x/TiN analog artificial synapse memristor is designed and investigated. With the increase of compliance current (C. C.) under 0.6 mA, 1 mA, and 3 mA, the current in the high resistance state (HRS) presents an increasing variation, which indicates lithium ions participates in the operation process for Pt/LiSiO_x/TiN memristor. Moreover, depending on the movement of lithium ions in the functional layer, the memristor illustrates excellent conduction modulation property, so the long-term potentiation (LTP) or depression (LTD) and paired-pulse facilitation (PPF) synaptic functions are successfully achieved. The neural network simulation for pattern recognition is proposed with the recognition accuracy of 91.4%. These findings suggest the potential application of the LiSiO_x memristor in the neuromorphic computing.     

Vibro-acoustic control with a distributed sensor network

The purpose of this work is to demonstrate the ability of a distributed control system, based on a smart sensor network, to reduce acoustic radiation from a vibrating structure. The platform from which control is effected consists of a network of smart sensors, each referred to as a node. Each node possesses its own computational capability, sensor, actuator and the ability to communicate with other nodes via a wired or wireless network. The primary focus of this work is to employ existing group management middleware concepts to enable vibro-acoustic control with such a distributed network. Group management middleware is distributed software that provides for the establishment and maintenance of groups of distributed nodes and that provides for the network communication among such groups. The control objective is met by designing distributed feedback compensators that take advantage of node groups in order to effect their control. The node groups are formed based on physical proximity. The global control objective is to minimize the radiated sound power from a rectangular plate. Results of this investigation demonstrate that such a distributed control system can achieve attenuations comparable to those achieved by a centralized controller.     

Analyzing the coexistence of DSRC and Wi-Fi networks using the Poisson line Cox process

Vehicular networks can aid in traffic monitoring, autonomous driving, and car accidents prevention. Yet, the deployment of these networks has been delayed due to the limited spectrum, especially for the case of unlicensed operations. To handle this issue, the Federal Communications Commission (FCC) proposed to permit Wi-Fi devices to operate in the 5.9 GHz band allocated to the intelligent transportation system (ITS). In a recent work, we analyzed the impact of the coexistence of dedicated short range communications (DSRC) and Wi-Fi on future DSRC network deployments by developing a stochastic geometry analytical model that considers a dynamic medium access probability (MAP) of DSRC nodes which uses carrier sense multiple access with collision avoidance (CSMA/CA). This previous work was based on the standard 2D homogeneous Poisson Point Process (PPP) model. In this work, we model the roads using the more applicable but more complex Poisson line process (PLP) Cox point process. We generate performance metrics represented through coverage probability and area system throughput, and we compare these results to our earlier work. The importance of this work is two-fold. First, it allows a further understanding of the impact of DSRC-Wi-Fi coexistence on future DSRC network deployments, and second, it highlights the effectiveness of the PLP in modeling the distribution of vehicles in an area by producing more accurate performance results.     

Group mobility assisted network selection framework in 5G vehicular cognitive radio networks

The heterogeneity nature of networks is the most eminent characteristic in 5G vehicular cognitive radio networks across complex radio environments. Since multiple communicating radios may be in motion at the same time in a vehicle. So, group mobility is the most prominent characteristic that requires to be a deep investigation. Therefore, different communication radios that are moving on a train/bus needed to select the networks simultaneously. Without considering the group mobility feature, there is a possibility that the same network may be selected by each moving node and cause congestion in a particular network. To overcome this problem, a novel network selection technique considering the group mobility feature is proposed to improve the throughput of the network. In this work, a 5G vehicular cognitive radio network scenario is also realized using USRP-2954 and LabVIEW communications system design suite testbed. The performance metrics like transmission delay, packet loss rate, reject rate and, channel utilization for vehicular nodes, are gained to analyze the proposed technique in vehicular cognitive radio networks environment. The proposed technique demonstrates a remarkable improvement in channel utilization for vehicular nodes and outperformed conventional schemes.     

基于演化博弈的社交网络模型演化研究

社会网络研究的兴起,为网络演化规律研究提供了有效工具,但大多数研究集中从宏观机制评估网络演化的动态过程. 本文基于公共品博弈,通过演化博弈与网络拓扑共演化方式,从微观角度提出了多社区动态网络演化模型（dMCPGG）. 即以节点间演化博弈为动力,修改节点间边的关系,驱动网络拓扑演化. 考虑到网络异质性,采用基于拓扑势的偏好规则更准确全面的描述节点影响力. 通过数值模拟和仿真实验,验证了本模型的合理性,不仅重现了无标度网络及随机网络的节点度、聚类系数及平均路径长度的结构特性,还准确捕捉到真实社交网络的演化过程. 关键词： 公共品博弈 拓扑势 偏好选择 共演化     

Optimal design of 32 channels spectrum slicing WDM for optical fiber access network system

In this article, the spectrum sliced dense wavelength division multiplexed passive optical network (SS-DWDM–PON) has been investigated as a power efficient and cost effective solution for optical access networks. In this work an AWG demultiplexer is used to operate as slicing system. The high speed SS-DWDM system has been realized and investigated for 32 channels with data rate up to 3 Gb/s using broadband ASE source (LED). The 3 Gb/s signals both non-return-to-zero (NRZ) and return-to-zero (RZ) were demonstrated in 40 km optical fiber link with BER < 10⁻¹². The results obtained here demonstrate that SS-DWDM is well suited for Fiber-to-the-Home (FTTH) network.     

Complex network study of Asian Go players

Tournaments of the game of Go can be represented as a directed network in which the vertices are players and a directed link is pointing from the winner to the loser for each game. In this article, we present some interesting results for the network of Asian Go players, which is composed of 756 Go players and 9473 tournaments. It is found that the topological structure of this network displays the small-world property and a significant rich-club phenomenon where high-degree nodes are tightly interconnected. In addition, we consider the weighted version of the network, and find the weights obey power-law distributions, while the strengths follow stretched exponential distributions. The time evolution of the network structure is studied and the corresponding results discussed. The analysis of this work provides a deeper understanding for the competition network structure of Asian Go players.     

Optimization of network structure to random failures

Network's resilience to the malfunction of its components has been of great concern. The goal of this work is to determine the network design guidelines, which maximizes the network efficiency while keeping the cost of the network (that is the average connectivity) constant. With a global optimization method, memory tabu search (MTS), we get the optimal network structure with the approximately best efficiency. We analyze the statistical characters of the network and find that a network with a small quantity of hub nodes, high degree of clustering may be much more resilient to perturbations than a random network and the optimal network is one kind of highly heterogeneous networks. The results strongly suggest that networks with higher efficiency are more robust to random failures. In addition, we propose a simple model to describe the statistical properties of the optimal network and investigate the synchronizability of this model.