双向联想记忆神经网络的一种编码策略

本文提出一种双向联想记忆神经网络的按‘位’加权编码策略，并给出了求取权值递推算法，它将Ｋｏｓｋｏ双向联想记忆网络按海明距离进行模式匹配的原则，修正了按加权海明距离进行了模式匹配，从而可以使得对不满足加续性的所谓“病态结构”的一类样本模式集，同样具有良好的联想能力，对二值图象模式存贮，联想的计算机模拟实验表明，此方法具有优良的性能和实用价值。     

Towards Unique and Anchor-Free Localization for Wireless Sensor Networks

Despite a large number of approaches developed for wireless sensor network (WSN) localization, there are still many unsolved problems in this area. The challenges to be addressed are both in analyzing characteristics of the localizable WSNs and designing efficient localization algorithms under a variety of conditions. In this paper we first draw on powerful results from graph rigidity theory and combinatorial theory, revealing that the combination of distance constraint and bearing constraint leads to necessary and sufficient condition for unique localization. This enlightens our proposing an anchor-free and computationally simple ad hoc localization algorithm for WSNs. A novel combination of distance and direction estimation technique is introduced to detect and estimate ranges between neighbors. Using this information we construct unidirectional local coordinate systems to avoid the reflection ambiguity. Such local maps then converge to form a global network wide coordinate system using a transformation matrix [T], which finally leads to node absolute positions. Simulation results have shown that our algorithm achieves high accuracy without using any error refining schemes.     

Guaranteed recall of all training pairs for exponentialbidirectional associative memory

Several methods of guaranteeing the recall of all training pairs for exponential bidirectional associative memory are presented. If the minimum Hamming distance between patterns is known, the radix can be determined to provide a certain basin of attraction. Otherwise the statistical minimum distance can be applied. A weight learning algorithm based on a pseudo-relaxation algorithm is also developed to make all training pairs recallable with a small radix     

Decoding algorithm and architecture for BCH codes under the Lee Metric

The Lee metric measures the circular distance between two elements in a cyclic group and is particularly appropriate as a measure of distance for data transmission under phase-shift-keying modulation over a white noise channel. In this paper, using newly derived properties on Newton?s identities, we initially investigate the Lee distance properties of a class of BCH codes and show that (for an appropriate range of parameters) their minimum Lee distance is at least twice their designed Hamming distance. We then make use of properties of these codes to devise an efficient algebraic decoding algorithm that successfully decodes within the above lower bound of the Lee error-correction capability. Finally, we propose an attractive design for the corresponding VLSI architecture that is only mildly more complex than popular decoder architectures under the Hamming metric; since the proposed architecture can also be used for decoding under the Hamming metric without extra hardware, one can use the proposed architecture to decode under both distance metrics (Lee and Hamming).     

Conservative arrays: multidimensional modulation codes forholographic recording

In holographic storage, two-dimensional arrays of binary data is optically recorded in a medium via an interference process. To ensure optimum operation of a holographic recording system, it is desirable that the patterns of 1s (light) and 0s (no light) in the recorded array satisfy the following modulation constraint: in each row and column of the array there are at least t transitions of the type 1→0 or 0→1, for a prescribed integer t. A two-dimensional array with this property is said to be a conservative array of strength t. In general, an n-dimensional conservative array of strength t is a binary array having at least t transitions in each column, extending in any of the n dimensions of the array. We present an algorithm for encoding unconstrained binary data into an n-dimensional conservative array of strength t. The algorithm employs differential coding and error-correcting codes. Using n binary codes-one per dimension-with minimum Hamming distance d⩾2t-3, we apply a certain transformation to an arbitrary information array which ensures that the number of transitions in each dimension is determined by the minimum distance of the corresponding code     

A New Linear Programming Approach to Decoding Linear Block Codes

In this paper, we propose a new linear programming formulation for the decoding of general linear block codes. Different from the original formulation given by Feldman, the number of total variables to characterize a parity-check constraint in our formulation is less than twice the degree of the corresponding check node. The equivalence between our new formulation and the original formulation is proven. The new formulation facilitates to characterize the structure of linear block codes, and leads to new decoding algorithms. In particular, we show that any fundamental polytope is simply the intersection of a group of the so-called minimum polytopes, and this simplified formulation allows us to formulate the problem of calculating the minimum Hamming distance of any linear block code as a simple linear integer programming problem with much less auxiliary variables. We then propose a branch-and-bound method to compute a lower bound to the minimum distance of any linear code by solving a corresponding linear integer programming problem. In addition, we prove that, for the family of single parity-check (SPC) product codes, the fractional distance and the pseudodistance are both equal to the minimum distance. Finally, we propose an efficient algorithm for decoding SPC product codes with low complexity and maximum-likelihood (ML) decoding performance.      

Optimal binary vector quantization via enumeration of coveringcodes

Binary vector quantization (BVQ) refers to block coding of binary vectors under a fidelity measure. Covering codes were studied as a means of lattice BVQ. But a further source coding problem hidden in the equivalence of covering codes has seemingly eluded attention. Given a d-dimensional hypercube (code space), equivalent covering codes of the same covering radius but of different codewords have different expected BVQ distortions for a general probability mass function. Thus one can minimize, within the code equivalence, the expected distortion over all different covering codes. This leads a two-stage optimization scheme for BVQ design. First we use an optimal covering code to minimize the maximum per-vector distortion at a given rate. Then under the minmax constraint, we minimize the expected quantization distortion. This minmax constrained BVQ method (MCBVQ) controls both the maximum and average distortions, and hence improves subjective quality of compressed binary images, MCBVQ also avoids poor local minima that may trap the generalized Lloyd method. The [7,4] Hamming code and [8,4] extended Hamming code are found to be particularly suitable for MCBVQ on binary images. An efficient and simple algorithm is introduced to enumerate all distinct [7,4] Hamming/[8,4] extended Hamming codes and compute the corresponding expected distortions in optimal MCBVQ design. Furthermore, MCBVQ using linear covering codes has a compact codebook and a fast syndrome-encoding algorithm     

主瓣干扰下多点约束自适应单脉冲测角方法

当存在主瓣干扰的情况下,采用常规的自适应波束形成技术会使单脉冲曲线严重失真,从而导致无法对感兴趣的目标正常测角及跟踪。为了在抑制主瓣干扰的同时能基本保持自适应单脉冲比曲线不失真,提出了一种基于多点约束的自适应单脉冲测角方法,该方法采用约束自适应波束形成技术,即在自适应抑制干扰的同时选取多个约束点对用于测角的单脉冲比进行约束,从而大大提高了存在主瓣干扰下单脉冲测角的性能。计算机仿真实验证明了该方法的有效性。     

On Justesen’s algebraic geometry codes

An isomorphism preserving Hamming distance between two algebraic geometry (AG) codes is presented to obtain the main parameters of Justesen’s algebraic geometry (JAG) codes. To deduce a simple approach to the decoding algorithm, a code word in a “small” JAG code is used to correspond to error-locator polynomial. By this means, a simple decoding procedure and its ability of error correcting are explored obviously. The lower and upper bounds of the dimension of AG codes are also obtained.     

Geometrical and performance analysis of GMD and Chase decodingalgorithms

The overall number of nearest neighbors in bounded distance decoding (BDD) algorithms is given by N_0,eff=N₀+N _BDD. Where NBDD denotes the number of additional, non-codeword, neighbors that are generated during the (suboptimal) decoding process. We identify and enumerate the nearest neighbors associated with the original generalized minimum distance (GMD) and Chase (1972) decoding algorithms. After careful examination of the decision regions of these algorithms, we derive an approximated probability ratio between the error contribution of a noncodeword neighbor (one of N_BDD points) and a codeword nearest neighbor. For Chase algorithm 1 it is shown that the contribution to the error probability of a noncodeword nearest neighbor is a factor of 2^d-1 less than the contribution of a codeword, while for Chase algorithm 2 the factor is 2^[d/2]-1, d being the minimum Hamming distance of the code. For Chase algorithm 3 and GMD, a recursive procedure for calculating this ratio, which turns out to be nonexponential in d, is presented. This procedure can also be used for specifically identifying the error patterns associated with Chase algorithm 3 and GMD. Utilizing the probability ratio, we propose an improved approximated upper bound on the probability of error based on the union bound approach. Simulation results are given to demonstrate and support the analytical derivations     

OFDM系统降低峰平比方法的研究

采用部分传输序列(PTS)降低OFDM系统中的峰平比.虽然PTS法具有不会使信号发生畸变,应用不受载波数限制,频谱损失小等优点,但是其实现起来计算量较大,限制了它在实际中的应用.在充分研究了基于汉明距离的PTS算法后,在其中加入门限值,仿真证明这种方法在不损失PAPR性能的前提下,可以进一步降低复杂度,具有较强的实用性.     

结合预确定距离的BIST测试矢量优化

在分析和介绍了海明距离与笛卡尔距离的基础上,通过改进细胞自动机生成的测试矢量间的链接性,提出了结合预确定距离的测试矢量优化方法.该方法通过设计最大海明距离和笛卡尔距离构造预确定距离序列,并利用遗传算法的全局寻优得到最佳预确定测试序列.通过ISCSA’85实验结果表明,该方法生成的预确定测试矢量比LFSR-CA结构的测试方法有更高的故障覆盖率和测试效率,在检测难测故障中效果更明显.     

Optimum Frame Synchronization for Biorthogonally Coded Data

The optimum procedure for locating a sync word periodically inserted in uncoded binary data received over a binary symmetric channel is based on the Hamming or bit distance metric. This concise paper addresses the corresponding frame-sync problem for biorthogonally coded data transmitted over the additive white Gaussian noise (AWGN) channel. For conceptual convenience, thek-bit words from the decoder output are treated as "super symbols" from an alphabet of dimension 2^k. It is argued that the optimum sync-word search over the decoded data stream is based on a supersymbol distance rule matched to the properties of the biorthogonally coded transmissions over the noisy channel. An optimum frame-sync acquisition algorithm based on this distance rule is formulated, and its performance is investigated. As an example, the performance of this optimum frame-sync algorithm is contrasted analytically with that of a Hamming distance algorithm operating on decoded (32, 6) biorthogonal data, a case of interest to some recent unmanned American space missions.     

多样性检测器生成算法研究

文章基于小生境策略的否定选择算法利用在搜索空间中计算检测器之间的海明距离,构建小生境;定义适应度函数与亲合力函数相关,更客观地反映检测器的检测能力;利用进化策略,进行遗传操作,而生成多样性和通用性的最佳检测器集。同时该算法可以减少生成检测器的时间开销。     

Error-erasure decoding of product codes (Corresp.)

Two error-erasure decoding algorithms for product codes that correct all the error-erasure patterns guaranteed correctable by the minimum Hamming distance of the product code are given. The first algorithm works when at least one of the component codes is majority-logic decodable. The second algorithm works for any product code. Both algorithms use the decoders of the component codes.     

A self-learning neural network chip with 125 neurons and 10 Kself-organization synapses

A learning neural network LSI chip is described. The chip integrates 125 neuron units and 10K synapse units with the 1.0 μm double-poly-Si, double-metal CMOS technology. Most of this integration has been realized by using a mixed design architecture of digital and analog circuits. The fully feedback connection network LSI can memorize at least 15 patterns with 50 μs learning time for each pattern. Under the condition that each test vector keeps a Hamming distance of 6 from memorized pattern, a correct association rate of 98% is obtained. The relaxation time is 1 to 2 μs. This chip consumes less than 7.5 W     

Algorithmic construction of trellis codes

An algorithmic approach is proposed whereby long convolutional codes of rate r_c=k/n can easily be constructed for any chosen signal constellation in signal space. These algorithms are iterative, and in each step a number of candidate codes are found which locally maximize the distance (Hamming or Euclidean) between the codewords. The result is not necessarily a free-distance-optimizing code. However, since the construction complexity can be chosen, optimal codes are quite frequently found. The codes ae constructed such that a rapid growth of the column distance is achieved. A method of combining two codes into a single code of twice the constraint length is also presented     

Performance Evaluation of a Virtual Queuing – Channel Allocation Scheme for Microcellular Networks

This paper deals with the performance evaluation of a novel distributed channel allocation scheme that attains a high resource reuse in cellular networks. A suitable interference model has been envisaged. Resources are nominally assigned to cells with Fixed Channel Allocation (FCA), according to a given reuse distance. Whenever a channel demand from a mobile user does not find a free nominal resource in a cell, a channel is temporarily borrowed violating the reuse distance constraint, provided that the co-channel interference level is acceptable. As soon as a nominal channel becomes available in this cell, the borrowed resource is released (virtual queuing). The performance of the proposed channel allocation scheme has been evaluated considering both uniform and non-uniform traffic patterns. A performance analysis approach has been also developed and validated by simulations. Comparisons with the classical FCA scheme and other dynamic and borrowing channel allocation strategies have permitted to highlight the good performance of the proposed technique.     

Algorithm for mapping between information bits and channel symbolsin MTCM codes

An algorithm for mapping between information bits and channel symbols in multiple trellis-coded modulation (MTCM) codes with M-PSK signal sets is proposed. The core of the algorithm assigns information bits with a Hamming distance in proportion to the sum of the Euclidean distance to each M-PSK symbol. The analytical results show that the additional gains from applying the algorithm can be achieved with little or no loss     

基于PEG算法的QC-LDPC码构造

提出一种QC-LDPC码的构造方法,这种方法利用受约束的PEG算法构造一个符合给定度分布的LDPC码基矩阵,能够保证构造出来的LDPC码短环的数量比较少,且具有线性时间编码.该方法在基矩阵的基础上利用缩短RS码集合的构造方法得到对应位置的偏移地址,以保证所构造的LDPC码的最小码距.最后给出构造的QC-LDPC码与DV...