Architecture research and hardware implementation on simplified neural computing system for face identification

This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic pattern recognition has been embedded. For the total 1200 tests for face identification, the false rejection rate is 3.7% and the false acceptance rate is 0.7%.

Quantum computing

Quantum computing is a quickly growing research field. This article introduces the basic concepts of quantum computing, recent developments in quantum searching, and decoherence in a possible quantum dot realization.

Formalization and specification for controlling process modularity in mobile computing

新的计算模式，普适计算和全局计算，正在作为高度分布式和移动计算的计算模式展现出来。这篇论文探讨了在抽象层面上支持这些新型计算模式的适合的形式化基础，关注在进程移动单位上的控制, 以便在分布式与移动计算环境下更好地协调进程的移动性。 论文的第一部分概述了针对分布式、移动计算的现有进程演算模型中的进程移动单元，并且设计了一种在此方面更优、更具弹性的进程框架。为了表示这种进程框架，我们提出了一种新的、针对移动和分布式系统的进程演算,这种进程演算的优点是动态、弹性的控制进程的移动单元；具体的思路就是扩展π- calculus以及其支持分布式和移动性的变体。我们把这种新的演算叫做Modular π-calculus。我们通过这种演算的提出来说明进程框架提供了一种针对移动进程更为合适的协调机制以及编程模型，例如移动的代理和动态组件载入的支持。之后，我们通过讨论互模拟的几种提法来具体说明能够反映演算设计的进程描述的关键，之后我们讨论了它们的具体性质。 本文的第二部分提出了一个对进程模型的行为和性质进行推理的规约框架。首先，提出了一个对Modularπ-calculus中进程的系统性质进行规约的模态逻辑。为了更好的理解该逻辑，文中对由这个逻辑推出的进程等价的特征进行了研究，并且证明了该逻辑的区分能力介于互模拟和结构一致之间。接下来关于这个规约框架的自动化，本文针对该逻辑和Modular π-calculus的有限控制子集，提出了模型检测算法，并且给出了算法正确性的证明。同时文中贯穿了一些实际且直观的例子，以展现本文提出的一组框架即演算、逻辑和模型算法的有效性。

algorithms for computing weak bisimulation equivalence

IEEE Comp Soc, IFIP, Tianjin Normal Univ

Atom space distance and computing of molecular similarity

A mathematical model on computation of molecular similarity was suggested, The algorithmic techniques for measuring the degree of similarity between pairs of three-dimensional chemical molecules was represented by modified interatomic distance matrices. Current work was carried out on Indigo 2 work station with Sybyl software. Four groups of molecules were used to compute the molecules similarity to testing the mathematical model with satisfactory results.

基于波动方程的层间多次波预测方法研究

In exploration geophysics，velocity analysis and migration methods except reverse time migration are based on ray theory or one-way wave-equation. So multiples are regarded as noise and required to be attenuated. It is very important to attenuate multiples for structure imaging, amplitude preserving migration. So it is an interesting research in theory and application about how to predict and attenuate internal multiples effectively. There are two methods based on wave-equation to predict internal multiples for pre-stack data. One is common focus point method. Another is inverse scattering series method. After comparison of the two methods, we found that there are four problems in common focus point method: 1. dependence of velocity model; 2. only internal multiples related to a layer can be predicted every time; 3. computing procedure is complex; 4. it is difficult to apply it in complex media. In order to overcome these problems, we adopt inverse scattering series method. However, inverse scattering series method also has some problems: 1. computing cost is high; 2. it is difficult to predict internal multiples in the far offset; 3. it is not able to predict internal multiples in complex media. Among those problems, high computing cost is the biggest barrier in field seismic processing. So I present 1D and 1.5D improved algorithms for reducing computing time. In addition, I proposed a new algorithm to solve the problem which exists in subtraction, especially for surface related to multiples. The creative results of my research are following: 1. derived an improved inverse scattering series prediction algorithm for 1D. The algorithm has very high computing efficiency. It is faster than old algorithm about twelve times in theory and faster about eighty times for lower spatial complexity in practice; 2. derived an improved inverse scattering series prediction algorithm for 1.5D. The new algorithm changes the computing domain from pseudo-depth wavenumber domain to TX domain for predicting multiples. The improved algorithm demonstrated that the approach has some merits such as higher computing efficiency, feasibility to many kinds of geometries, lower predictive noise and independence to wavelet； 3. proposed a new subtraction algorithm. The new subtraction algorithm is not used to overcome nonorthogonality, but utilize the nonorthogonality's distribution in TX domain to estimate the true wavelet with filtering method. The method has excellent effectiveness in model testing. Improved 1D and 1.5D inverse scattering series algorithms can predict internal multiples. After filtering and subtracting among seismic traces in a window time, internal multiples can be attenuated in some degree. The proposed 1D and 1.5D algorithms have demonstrated that they are effective to the numerical and field data. In addition, the new subtraction algorithm is effective to the complex theoretic models.