怎样设计一个八位数码的奇偶校验电路

《数学电子技术基础》第三章(题3-9),要求设计一个八位数码的奇偶校验电路。下面将设计八位数码的奇偶校验电路作为一题多解的实例来讨论。一、分析设计要求将输入变量数用ABCDEFGH表示,输出用Y表示,其方框图如图1所示。当输入变量ABCDEFGH中包含偶数个1时,则Y=1,否则Y=0。二、设计方案(一)用与非门来实现,有两种解法:

基于SET/MOS混合结构的奇偶校验码产生电路的设计

基于单电子晶体管(SET)的库仑振荡效应和多栅输入特性,利用SET和金属氧化物半导体场效应晶体管(MOS管)的互补特性,设计了基于SET/MOS混合电路的奇偶校验码产生电路。利用HSPICE对所设计电路进行仿真验证,结果表明,该电路能够实现产生奇偶校验码的功能。该SET/MOS混合电路的实现只需要1个PMOS管、1个NMOS和1个多栅输入SET。与传统CMOS电路相比,SET/MOS混合电路使用的管子数目大大减少,功耗显著降低。

数字电路中毛刺噪声的防治

在进行数字电子产品研制过程中,必然会遇到各种各样的噪声。为了揭示毛刺噪声的根源,通过实验对传输信号中的毛刺噪声波形进行反复比较。采用奇/偶校验器来检测信号传输过程中毛刺噪声是否存在。采用两种主要方法消灭毛刺噪声:(1)应用选通脉冲和"与门"电路来恢复尖峰噪声中的理想脉冲信号。(2)用RC积分电路削弱毛刺噪声。实践中,使用这些措施去抑制数码电子产品的毛刺噪声,都达到了事半功倍的效果。

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.

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.

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.

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.