A New Feedback-feedforward Configuration for the Iterative Learning Control of a Class of Discrete-time Systems

这份报纸为反复的学习控制(ILC ) 论述一种新反馈前馈控制配置与反馈设计，它由反馈和一个前馈控制部件组成。反馈积分控制器稳定系统，并且在操作，和前馈控制 ILC 期间起主导的作用补偿可重复的非线性 / 未知的变化时间的动力学和骚乱，从而提高性能独自由反馈控制完成了。作为这控制策略的最有利的点，没有作努力到前馈控制 / 反馈获得的 reconfigurate 或重新调律，前馈控制 ILC 和反馈控制能独立地或联合工作。与严密分析，建议学习控制计划沿着重复轴保证 asymptotic 得到集中。

Low Complexity Multiuser Detection with Recursively Successive Zero-Forcing and SIC Based on Nullspace for Multiuser MIMO-OFDM System

To improve the spectrum efficiency, this paper considers the multiuser detection with the MU-MIMO technology for multiuser MIMO-OFDM system uplink with the same subcarrier shared by multiple users. A low complexity multiuser detection algorithm with recursively successive zero-forcing and successive interference cancellation(RSZF-SIC) based on nullspace is proposed. The RSZF process based on the block diagonalization(BD) technique eliminates the co-channel interference(CCI) by a recursive method based on the nullspace orthogonal theorem. The SIC process detects the user signals respectively with the reasonable user detection sequence based on the results of the RSZF process. The computational complexity of the proposed algorithm is effectively reduced by reducing the total number of singular value decomposition(SVD) operations and the dimension of the SVD matrix in the recursive procedure. The performance of the proposed algorithm is improved in terms of bit error rate and sum capacity of the system, especially in the highSNR regime.

Norm-Based Adaptive Coefficient ZNN for Solving the Time-Dependent Algebraic Riccati Equation

Dear Editor, The time-dependent algebraic Riccati equation(TDARE) problem is applied to many optimal control industrial applications. It is susceptible to interference from measurement noises in the virtual environment, which current methods cannot effectively address. A normbased adaptive coefficient zeroing neural network(NACZNN) model to solve the TDARE problem is proposed.

A Short-Term Precipitation Prediction Model Based on Spatiotemporal Convolution Network and Ensemble Empirical Mode Decomposition

Dear editor,Regional precipitation,as a very important component system of hydrology,plays a key role in the whole water cycle[1].The dramatic changes of regional precipitation in a short period can easily have a serious impact on the local ecological environment and daily life.Short-term heavy precipitation refers to precipitation events with rainfall of more than 20 mm in one hour or 50 mm in three hours[2].Therefore,how to accurately and timely predict future precipitation is an important research field in meteorology.However,precipitation prediction has always been a challenging task because of its complex spatial and temporal dependence.

An Exponential Chaotic Oscillator Design and Its Dynamic Analysis

After years of development, chaotic circuits have possessed many different mathematic forms and multiple realization methods. However, in most of the existing chaotic systems, the nonlinear units are composed of the product terms. In this paper, in order to obtain a chaotic oscillator with higher nonlinearity and complexity to meet the needs of utilization, we discuss a novel chaotic system whose nonlinear term is realized by an exponential term. The new exponential chaotic oscillator is constructed by adding an exponential term to the classical Lüsystem. To further investigate the dynamic characteristics of the oscillator, classical theoretical analyses have been performed, such as phase diagrams, equilibrium points, stabilities of the system,Poincaré mappings, Lyapunov exponent spectrums, and bifurcation diagrams. Then through the National Institute of Standards and Technology(NIST) statistical test, it is proved that the chaotic sequence generated by the exponential chaotic oscillator is more random than that produced by the Lü system. In order to further verify the practicability of this chaotic oscillator, by applying the improved modular design method, the system equivalent circuit has been realized and proved by the Multisim simulation. The theoretical analysis and the Multisim simulation results are in good agreement.

IMPROVEMENT OF TCAM-BASED PACKET CLASSIFICATION ALGORITHM

The feature of Ternary Content Addressable Memories(TCAMs) makes them particularly attractive for IP address lookup and packet classification applications in a router system. However,the limitations of TCAMs impede their utilization. In this paper,the solutions for decreasing the power consumption and avoiding entry expansion in range matching are addressed. Experimental results demonstrate that the proposed techniques can make some big improvements on the performance of TCAMs in IP address lookup and packet classification.

Wireless Body Area Networks for Pervasive Healthcare and Smart Environments

Wireless body area networks （WBANs） use RF communication for interconnection of tiny sensor nodes located in, on, or in close prox- imity to the human body. A WBAN enables physiological signals, physical activity, and body position to be continuously monitored.

Event-Triggered Differentially Private Average Consensus for Multi-agent Network

This paper investigates the differentially private problem of the average consensus for a class of discrete-time multi-agent network systems(MANSs). Based on the MANSs,a new distributed differentially private consensus algorithm(DPCA) is developed. To avoid continuous communication between neighboring agents, a kind of intermittent communication strategy depending on an event-triggered function is established in our DPCA. Based on our algorithm, we carry out the detailed analysis including its convergence, its accuracy, its privacy and the trade-off between the accuracy and the privacy level, respectively. It is found that our algorithm preserves the privacy of initial states of all agents in the whole process of consensus computation. The trade-off motivates us to find the best achievable accuracy of our algorithm under the free parameters and the fixed privacy level. Finally, numerical experiment results testify the validity of our theoretical analysis.

A Near Optimal Power Allocation Scheme for Cooperative Relay Networking with NOMA

In this paper, we propose cooperative relay networks with non-orthogonal multiple access in order to design a near-optimal power allocation strategy. Like other next generation wireless technologies, spatially multiplexed transmissions are achieved by relay nodes which enables decode-and-forward relaying of a new superposition code after reception from the source. It is worth noting that, since it is hard to exactly prove the proposed PA scheme, due the fact that it is one kind of the approximate conjectures. Therefore, mathematical and numerical methods have been used to clarify the feasibility of the proposal. Numerical results indicate that it is able to asymptotically achieve the optimal sum rate at the higher signal-to-noise ratio region with the proposed strategy applied instead of negligible performance loss.

Edge Intelligence for 6G Networks

With the rapid development of smart terminals and infrastructures,as well as diversified applications(e.g.,autonomous driving,virtual and augmented reality,space-air-ground integrated networks)with colorful demands,current networks(e.g.,4G and 5G networks)may not be well suited to the requirements of novel applications and services.Recently,efforts from both the industry and academia have been made on the research into 6G networks,artificial intelligence(AI)will play a pivotal role in the design and optimization of 6G networks.

A less complicated adaptive equalization for UWB channels

In this paper,a new adaptive equalization scheme aiming at the intersymbol and interuser interfer-ences in the multiuser ultra-wide band(UWB)channels is presented specially for direct-sequence UWB/time-hopping UWB(DS-UWB/TH-UWB)receivers.Its computational complexity and convergence rate are compared with the conventional algorithms.The simulation results show that the computational complexity of this scheme is less than employing the RLS method alone and the convergence rate of this scheme is farther off employing LMS method alone.