二进神经网络表达奇偶校验问题的隐元最小数目上界

二进神经网络采用线性分类,是结构简单又易于实现的一类神经网络,在许多应用领域中都有重要研究价值.对于单隐层二进神经网络,目前隐层规模的确定问题仍然没有明确的研究结论.本文在研究隐层规模问题的过程中,提出了布尔空间的最多孤立样本问题.在二进神经网络隐层神经元各自表达一个"与"关系,所有隐层神经元通过输出元形成"或"关系的情况下,证明了实现最多孤立样本问题需2n?1个隐层神经元.更重要的是,指出了n元奇偶校验问题和最多孤立样本结构的等价性.进一步地,通过引入隐层抑制神经元将隐元数目降为n,说明了抑制神经元在二进神经网络中的重要作用.最后,在Hamming球与SP函数的基础上,揭示出抑制神经元和n元奇偶校验问题的逻辑关系,并给出了奇偶校验问题的逻辑式表达.

LDPC Coding Scheme for Improving the Reliability of Multi-Level-Cell NAND Flash Memory in Radiation Environments

Utilizing commercial off-the-shelf(COTS) components in satellites has received much attention due to the low cost. However, commercial memories suffer severe reliability problems in radiation environments. This paper studies the low-density parity-check(LDPC) coding scheme for improving the reliability of multi-level-cell(MLC) NAND Flash memory in radiation environments. Firstly, based on existing physical experiment works, we introduce a new error model for heavyion irradiations; secondly, we explore the optimization of writing voltage allocation to maximize the capacity of the storage channel; thirdly, we design the degree distribution of LDPC codes that is specially suitable for the proposed model; finally, we propose a joint detection-decoding scheme based on LDPC codes, which estimates the storage channel state and executes an adaptive log-likelihood ratio(LLR) calculation to achieve better performance. Simulation results show that, compared with the conventional LDPC coding scheme, the proposed scheme may almost double the lifetime of the MLC NAND Flash memory in radiation environments.

无线语音／多媒体IP传输技术中首标压缩方案的研究

全IP的3G网络代表了移动通信网络发展的趋势。文中探讨了无线语音／多媒体IP传输技术中的首标压缩问题，给出了一种主要针对无线VIP／MIP的基于校验元的首标压缩方案以及相应仿真结果。

标准卷积码在QPSK相位模糊下的研究

在数字相位调制系统的相干解调过程中,普遍存在着载波相位模糊问题,以往的解决方法是遍历所有可能的相位模糊情况,通过解模糊处理、后续判断来验证每种可能的正确性,效率较低。针对QPSK解调过程中存在的8种相位模糊情况,利用卷积码编码约束关系,分析研究了标准(2,1,m)卷积码和各种码率的删余卷积码在每种相位模糊下其采样校验元的变化情况,以及相位模糊对译码后信息的影响,给出了基于采样校验元检测的相位模糊识别方法。该方法有效降低了相位模糊情况的可能数量,提高了人工观察判断的工作效率。

Shadow obstacle model for realistic corner-turning behavior in crowd simulation

This paper describes a novel model known as the shadow obstacle model to generate a realistic comer-tuming behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a comer. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic comer-turning behavior by comparison with real data obtained from the experiments. Finally, we per- form parameter analysis to show the believability of our model through a series of experiments.

Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember extraction

Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.

A survey of photon mapping state-of-the-art research and future challenges

Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.

Quantum-dot cellular automata based reversible low power parity generator and parity checker design for nanocommunication

Quantum-dot cellular automata （QCA） is an emerging area of research in reversible computing. It can be used to design nanoscale circuits. In nanocommunication, the detection and correction of errors in a received message is a major factor. Besides, device density and power dissipation are the key issues in the nanocommunication architecture. For the first time, QCA-based designs of the reversible low-power odd parity generator and odd parity checker using the Feynman gate have been achieved in this study. Using the proposed parity generator and parity checker circuit, a nanocommunication architecture is pro- posed. The detection of errors in the received message during transmission is also explored. The proposed QCA Feynman gate outshines the existing ones in terms of area, cell count, and delay. The quantum costs of the proposed conventional reversible circuits and their QCA layouts are calculated and compared, which establishes that the proposed QCA circuits have very low quantum cost compared to conventional designs. The energy dissipation by the layouts is estimated, which ensures the possibility ofQCA nano-device serving as an alternative platform for the implementation of reversible circuits. The stability of the proposed circuits under thermal randomness is analyzed, showing the operational efficiency of the circuits. The simulation results of the proposed design are tested with theoretical values, showing the accuracy of the circuits. The proposed circuits can be used to design more complex low-power nanoscale lossless cation architecture such as nano-transmitters and nano-receivers

Local uncorrelated local discriminant embedding for face recognition

The feature extraction algorithm plays an important role in face recognition. However, the extracted features also have overlapping discriminant information. A property of the statistical uncorrelated criterion is that it eliminates the redundancy among the extracted discriminant features, while many algorithms generally ignore this property. In this paper, we introduce a novel feature extraction method called local uncorrelated local discriminant embedding(LULDE). The proposed approach can be seen as an extension of a local discriminant embedding(LDE)framework in three ways. First, a new local statistical uncorrelated criterion is proposed, which effectively captures the local information of interclass and intraclass. Second, we reconstruct the affinity matrices of an intrinsic graph and a penalty graph, which are mentioned in LDE to enhance the discriminant property. Finally, it overcomes the small-sample-size problem without using principal component analysis to preprocess the original data, which avoids losing some discriminant information. Experimental results on Yale, ORL, Extended Yale B, and FERET databases demonstrate that LULDE outperforms LDE and other representative uncorrelated feature extraction methods.

Design and simulation of a standing wave oscillator based PLL

A standing wave oscillator(SWO) is a perfect clock source which can be used to produce a high frequency clock signal with a low skew and high reliability. However, it is difficult to tune the SWO in a wide range of frequencies. We introduce a frequency tunable SWO which uses an inversion mode metal-oxide-semiconductor(IMOS) field-effect transistor as a varactor, and give the simulation results of the frequency tuning range and power dissipation. Based on the frequency tunable SWO, a new phase locked loop(PLL) architecture is presented. This PLL can be used not only as a clock source, but also as a clock distribution network to provide high quality clock signals. The PLL achieves an approximately 50% frequency tuning range when designed in Global Foundry 65 nm 1P9 M complementary metal-oxide-semiconductor(CMOS) technology, and can be used directly in a high performance multi-core microprocessor.

A consensus model for group decision making under interval type-2 fuzzy environment

We propose a new consensus model for group decision making(GDM) problems, using an interval type-2 fuzzy environment. In our model, experts are asked to express their preferences using linguistic terms characterized by interval type-2 fuzzy sets(IT2 FSs), because these can provide decision makers with greater freedom to express the vagueness in real-life situations. Consensus and proximity measures based on the arithmetic operations of IT2 FSs are used simultaneously to guide the decision-making process. The majority of previous studies have taken into account only the importance of the experts in the aggregation process, which may give unreasonable results. Thus, we propose a new feedback mechanism that generates different advice strategies for experts according to their levels of importance. In general, experts with a lower level of importance require a larger number of suggestions to change their initial preferences. Finally, we investigate a numerical example and execute comparable models and ours, to demonstrate the performance of our proposed model. The results indicate that the proposed model provides greater insight into the GDM process.