Modeling robust asynchronous communication protocols withfinite-state machines

A.V. Aho et al. (Comput. Math. Applic., vol.8, p.205-14, 1982) used communicating finite-state machines to model synchronous protocols for reliable communication across unreliable channels. Their ideas are extended to modeling asynchronous protocols for communication across unreliable channels using finite-state machines communicating via an unreliable shared memory. Lower bounds on the size of machines and the number of symbols in the transmission alphabet required to achieve reliable communication are established. Two types of finite-state machines and two fault models for the shared memory are considered. In each case it is shown that there are robust protocols for deletion and insertion errors. It is also shown that there are no robust protocols for mutation errors. In contrast, in the synchronous case, robust protocols exist for all of these types of errors     

On maximum-likelihood detection and decoding for space-time codingsystems

Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have been attracting increased attention. In this paper, we address two interrelated problems: detection of space-time codes under various interference conditions and information transfer from the STC detector to an error-correcting channel decoder. By taking a systematic maximum-likelihood (ML) approach to the joint detection and decoding problem, we show how to design optimal detectors and how to integrate them with a channel decoder. We also discuss various aspects of channel modeling for STC communication receivers. In particular, while many previous works on space-time coding assume that the channel is a stochastic quantity, we find that a deterministic channel model can have some advantages for the receiver design. Finally, we illustrate our results by numerical examples. Index Terms-Interference suppression, maximum-likelihood estimation, maximum-likelihood sequence detection, MIMO systems, space-time coding, soft information     

Networked Control for Singular Systems Over Unreliable Channel with Limited Capacity

This paper addresses networked control problem for discrete-time linear singular systems over unreliable channel. It is assumed that the controller can only receive the transmitted sequence of finite coded signals via unreliable channels, which may be lost due to the limited communication capacity and transmission errors. By introducing compensation terms at every update instant and auxiliary systems in each sampling interval, both state- and output-based coder–decoder–controller procedures are proposed. Then, a uniform sufficient feedback stabilization condition involving the size of coding alphabet, the sampling period and data packet dropout rate is obtained. Finally, an example is given to illustrate the design procedures and effectiveness of the proposed results.     

Real Time Fault Diagnosis with Tests of Uncertain Quality for Multimode Systems and its Application in a Satellite Power System

Dynamic fault diagnosis must consider complex fault situations such as fault evolution, coupling, unreliable tests and so on. Previous dynamic fault diagnostic models and inference algorithms are mainly designed for the steady state systems, which are not suitable for the multimode systems. In this paper, a time varying dynamic model to solve the multimode fault diagnosis problem is proposed. Its structure and formulation are presented. Fault diagnosis based on this model is realized by means of inference calculation given the test result, which is formulated as an optimization problem. A new algorithm to solve this problem is proposed. Simulation experiments on different scenarios are carried out to validate the model and the algorithm. As an example, the case of a satellite electrical power system is studied in detail. Both the simulation result and the application result show that the method proposed in this paper can be used to solve the dynamic fault diagnosis problem for multimode systems considering the complex circumstances such as uncertain tests and system delay.     

基于神经网络的纠错输出编码方法研究

构造基于数据编码矩阵是目前利用纠错输出编码解决多类分类问题的研究重点.为此提出利用单层感知器作为学习框架,结合解码策略把输出编码矩阵各码元值映射为感知器网络中的权值,同时引入含权值取值约束的目标函数作为该网络代价函数,并对其进行学习,最终得到基于子类划分的数据编码矩阵.实验中利用人工数据集和UCI数据集并选择线性逻辑分类器作为基分类器分别进行测试,通过与几种经典编码方法比较,结果表明该编码方法能在编码长度较小情况下得到更好的分类效果.     

Hidden Markov processes

An overview of statistical and information-theoretic aspects of hidden Markov processes (HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain observed through a discrete-time memoryless invariant channel. In recent years, the work of Baum and Petrie (1966) on finite-state finite-alphabet HMPs was expanded to HMPs with finite as well as continuous state spaces and a general alphabet. In particular, statistical properties and ergodic theorems for relative entropy densities of HMPs were developed. Consistency and asymptotic normality of the maximum-likelihood (ML) parameter estimator were proved under some mild conditions. Similar results were established for switching autoregressive processes. These processes generalize HMPs. New algorithms were developed for estimating the state, parameter, and order of an HMP, for universal coding and classification of HMPs, and for universal decoding of hidden Markov channels. These and other related topics are reviewed     

Towards Nanoelectronics Processor Architectures

In this paper, we focus on reliability, one of the most fundamental and important challenges, in the nanoelectronics environment. For a processor architecture based on the unreliable nanoelectronic devices, fault tolerance schemes are required so as to ensure the basic correctness of any computation. Since any fault tolerance approach demands redundancy either in the form of time or hardware, reliability needs to be considered in conjunction with the performance and hardware tradeoffs. We propose a new computational model for the nanoelectronics based processor architectures, that provides flexible fault tolerance to deal with the high and time varying faults. The model guarantees the correctness of instruction executions, while dynamically balancing hardware and performance overheads. The correctness of every instruction is confirmed by multiple execution instances through a hybrid hardware-time redundancy approach. To achieve high system performance, multiple unconfirmed computation branches are exploited in a speculative manner. Hardware resource growth that these speculative computations entail is controlled so that the utilization of hardware is balanced between the two competing goals of performance and fault tolerance. In addition, we examine the impact on the proposed computational model of other nanoelectronic characteristics such as the necessity for localization of interconnections and the regularity of nanofabric structures on the proposed computational model. We set up an experimental framework to validate the effectiveness of the proposed scheme as well as to investigate multiple tradeoff points within the proposed approach. Simulation data confirm that the proposed computational model achieves the goal of providing flexible fault tolerance under a wide range of fault occurrence rates, while at the same time guaranteeing high system performance and efficient utilization of hardware resources.     

RS码在空空导弹遥测系统中的应用

为了增强空空导弹遥测系统抗误码能力,使遥测数据传输更为可靠,需要在遥测系统弹栽部分采用纠错编码技术。根据空空导弹遥测系统的特点采用RS码作为遥测系统纠错编码,分析了RS码的编码原理及实现方法,探讨了数据交织与解交织的原理,介绍了遥测系统中RS码的应用方法。实验证明,在设计能力范围内,Rs码可正确恢复遥测数据传输过程中产生的误码,完全满足设计需求。     

A new multilevel coding method using error-correcting codes

A new multilevel coding method that uses several error-correcting codes is proposed. The transmission symbols are constructed by combining symbols of codewords of these codes. Usually, these codes are binary error-correcting codes and have different error-correcting capabilities. For various channels, efficient systems can be obtained by choosing these codes appropriately. Encoding and decoding procedures for this method are relatively simple compared with those of other multilevel coding methods. In addition, this method makes effective use of soft-decisions to improve the performance of decoding. The decoding error probability is analyzed for multiphase modulation, and numerical comparisons to other multilevel coding systems are made. When equally complex systems are compared, the new system is superior to other multilevel coding systems.     

Joint (3,k)-regular LDPC code and decoder/encoder design

Recently, low-density parity-check (LDPC) codes have attracted a lot of attention in the coding theory community. However, their real-world applications are still problematic mainly due to the lack of effective decoder/encoder hardware design approaches. In this paper, we present a joint (3,k)-regular LDPC code and decoder/encoder design technique to construct a class of (3,k)-regular LDPC codes that not only have very good error-correcting capability but also exactly fit to high-speed partly parallel decoder and low-complexity encoder implementations. We also develop two techniques to further modify this joint design scheme to achieve more flexible tradeoffs between decoder hardware complexity and decoding speed.     

Matrix Coded Modulation: A New Non-coherent MIMO Scheme

This paper describes a new space-time coding scheme for non-coherent multi-antenna Multi-Input Multi-Output (MIMO) systems. This new MIMO scheme merges error-correcting and space-time coding functions by transmitting invertible matrices, so this scheme has been called “Matrix Coded Modulation” or “MCM”. Coherent systems require Channel State Information (CSI) at the transmitters and/or at the receivers, and their performances strongly depend on the channel estimation. For example, in systems using Orthogonal Frequency Division Multiplexing, the channel estimation requires the insertion of pilot-symbols in the transmitted frame which implies a spectral efficiency loss of the global system that increase with the number of transmit antennas. The existing non-coherent schemes such as the Differential Space-Time Modulation leads to performance degradation compared to coherent systems in which perfect CSI is assumed. Decoding in the MCM scheme is performed iteratively, based on a specified detection criteria. In the proposed MCM scheme, decoding can be achieved with or without CSI at the receiving antennas. As the space-time coding function is merged with the error-correcting code, the euclidean distances distribution between modulated signals based on the detection criteria is strongly linked to the Hamming weights distribution of the channel error-correcting code used in the MCM scheme. Moreover, a low-complexity decoding algorithm is described and compared to the existing differential schemes.     

Matrix Coded Modulation: A New Non-coherent MIMO Scheme

This paper describes a new space-time coding scheme for non-coherent multi-antenna multi-input multi-output (MIMO) systems. This new MIMO scheme merges error-correcting and space-time coding functions by transmitting invertible matrices, so this scheme has been called “Matrix Coded Modulation” or “MCM”. Coherent systems require channel state information (CSI) at the transmitters and/or at the receivers, and their performances strongly depend on the channel estimation. For example, in systems using Orthogonal frequency division multiplexing, the channel estimation requires the insertion of pilot-symbols in the transmitted frame which implies a spectral efficiency loss of the global system that increase with the number of transmit antennas. The existing non-coherent schemes such as the differential space-time modulation leads to performance degradation compared to coherent systems in which perfect CSI is assumed. Decoding in the MCM scheme is performed iteratively, based on a specified detection criteria. In the proposed MCM scheme, decoding can be achieved with or without CSI at the receiving antennas. As the space-time coding function is merged with the error-correcting code, the euclidean distances distribution between modulated signals based on the detection criteria is strongly linked to the Hamming weights distribution of the channel error-correcting code used in the MCM scheme. Moreover, a low-complexity decoding algorithm is described and compared to the existing differential schemes.     

Delay-dependent fault detection for switched linear systems with time-varying delays—the average dwell time approach

In this paper, the fault detection problem is investigated for a class of discrete-time switched linear systems with time-varying delays. The main purpose is to design a fault detection filter such that, for all unknown inputs, control inputs and time delays, the estimation error between the residual and fault is minimized in an exponential way. The fault detection problem is converted into an exponential H_∞ filtering problem. By using a newly constructed Lyapunov functional and the average dwell time scheme, a novel delay-dependent sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities (LMIs). A numerical example is given to demonstrate the effectiveness of the developed theoretical results.     

Providing Real-Time Applications With Graceful Degradation of QoS and Fault Tolerance According to$(m, k)$-Firm Model

The$(m, k)$-firm model has recently drawn a lot of attention. It provides a flexible real-time system with graceful degradation of the quality of service (QoS), thus achieving the fault tolerance in case of system overload. In this paper, we focus on the distance-based priority (DBP) algorithm as it presents the interesting feature of dynamically assigning the priorities according to the system's current state (QoS-aware scheduling). However, DBP cannot readily be used for systems requiring a deterministic$(m, k)$-firm guarantee since the schedulability analysis was not done in the original proposition. In this paper, a sufficient schedulability condition is given to deterministically guarantee a set of periodic or sporadic activities (jobs) sharing a common non-preemptive server. This condition is applied to two case studies showing its practical usefulness for both bandwidth dimensioning of the communication system providing graceful degradation of QoS and the task scheduling in an in-vehicle embedded system allowing fault tolerance.     

太赫兹光谱数据库的建立和使用

为了将太赫兹光谱分析技术应用于物质识别领域,需要建立太赫兹波段的光谱数据库,并研究合适的数据库使用方法,以鉴别未知物质。光谱获取采用自行搭建的太赫兹时域光谱测量系统,通过小波变换去除基线和噪声等干扰信息,建立起含有20种典型有机物的光谱数据库。使用该数据库识别未知物质时,分成两步:1)用径向基函数神经网络算法判断未知物质是否在数据库中;2)若在数据库中,采用基于纠错输出编码的支持向量机多类算法鉴别物质种类。测试结果表明,对库内物质识别率为96.7%,对库外物质也有较好的预测和推断能力,识别率为93.2%。提出的太赫兹光谱数据库建立和使用方法,对系统噪声等干扰因素有很好的抑制作用,可以应用到实际场合。     

基于混沌的纠错编码设计和实现

本文在扩展卡尔曼滤波、混沌信号模拟调制,以及数字纠错编码的码距离度量等思想的基础上,设计和实现了一套基于混沌的模拟纠错编码/解码算法.仿真结果表明在低信噪比情况下,该算法有较强的纠错能力,优于传统的分组交织纠错编码.     

Conditional entropy-constrained residual VQ with application toimage coding

This paper introduces an extension of entropy constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements, moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.     

A geometric approach to fault detection and isolation of multi-dimensional (n-D) systems

Multidimensional Systems and Signal Processing - In this work, we develop a novel fault detection and isolation (FDI) scheme for discrete-time multi-dimensional (n-D) systems for the first time in...     

Block-LDPC: a practical LDPC coding system design approach

This paper presents a joint low-density parity-check (LDPC) code-encoder-decoder design approach, called Block-LDPC, for practical LDPC coding system implementations. The key idea is to construct LDPC codes subject to certain hardware-oriented constraints that ensure the effective encoder and decoder hardware implementations. We develop a set of hardware-oriented constraints, subject to which a semi-random approach is used to construct Block-LDPC codes with good error-correcting performance. Correspondingly, we develop an efficient encoding strategy and a pipelined partially parallel Block-LDPC encoder architecture, and a partially parallel Block-LDPC decoder architecture. We present the estimation of Block-LDPC coding system implementation key metrics including the throughput and hardware complexity for both encoder and decoder. The good error-correcting performance of Block-LDPC codes has been demonstrated through computer simulations. With the effective encoder/decoder design and good error-correcting performance, Block-LDPC provides a promising vehicle for real-life LDPC coding system implementations.     

一种新的适用于算法容错的加权校验和编码方案

基于算法的容错或算法容错是提高实时数字信号处理和其他大规模计算环境中并行系统可靠性的有效方案，本文讨论了一种新的具有高纠错能力的广义加权校验和编码方法，并进一步给出了快速的检测的检错纠错算法，最后讨论了新的编码方案在容错运算中的应用。