剖面隐马氏模型训练算法的改进

利用剖面隐马氏模型获得多序列联配，一般需要经过初始化、训练、联配三个过程．然而，目前广泛采用的Baum—welch训练算法假设各条可观察序列互相独立，这与实际情况有所不符．本文对剖面隐马氏模型，给出可观察序列在互相不独立情况下的改进Baum—wlelch算法，在可观察序列两种特殊情况下（互相独立和一致依赖），得到了改进算法的具体表达式，讨论了一般情况下权重的选取方法．最后通过一个具体的蛋白质家族的多序列联配来说明改进算法的效果．     

线性规划的约束条件“滚雪球”算法

为使线性规划的每个约束条件部分或全部地拥有原整个约束条件所包含的信息,将线性规划的约束条件“滚雪球”后得到与原约束条件等价的新约束条件,对新约束条件所构成的线性规划采用目标函数最速递减算法.有一定规模的随机数值算例显示了该算法只需进行m(约束条件数)次迭代即可求得最优解.     

A NEW ALGORITHM OF RELAXATION METHOD FOR PARTICLE ANALYSIS FROM FORWARD SCATTERED LIGHT

1. Introduction In many cases, particle dimension and size distribution play an important role in application. The analysis of parti- cle size is therefore necessary for research and develop- ment and also for process quality control in powder tech- nology and for many particle systems (Wang et al., 2000). Many instruments have been developed and constructed for this purpose. With the rapid development and availabil- ity of laser techniques, optoelectronics and microcomputer science, light sc…     

A polynomial-time algorithm for the change-making problem

Optimally making change—representing a given value with the fewest coins from a set of denominations—is in general NP-hard. In most real money systems however, the greedy algorithm is optimal. We give a polynomial-time algorithm to determine, for a given coin system, whether the greedy algorithm is optimal.     

An acyclic days-off scheduling problem

This paper studies the days off scheduling problem when the demand for staffing fluctuates from day to another and when the number of total workdays is fixed in advance for each employee. The scheduling problem is then to allocate rests to employees with different days off policies: (1) two or three consecutive days off for each employee per week and (2) at least three consecutive days off for each employee per month. For each one, we propose a polynomial time algorithm to construct a solution if it exists. Received: April 2005 / Revised version: October 2005 AMS classification: 60K25, 60K30     

Componentwise adaptation for high dimensional MCMC

Summary  We introduce a new adaptive MCMC algorithm, based on the traditional single component Metropolis-Hastings algorithm and on our earlier adaptive Metropolis algorithm (AM). In the new algorithm the adaption is performed component by component. The chain is no more Markovian, but it remains ergodic. The algorithm is demonstrated to work well in varying test cases up to 1000 dimensions.     

有预算限制的最大多种物资流问题

研究有预算限制的最大多种物资流问题,给出了这个问题的不依赖物资数k的全多项式时间近似算法,其算法复杂性是O~(-ε2m2).同时,利用有预算限制的最大多种物资流问题的研究结果,我们也得到了费用最小的最大多种物资流问题的近似算法和算法复杂性.     

Parallel computation of two-point boundary-value problems via particular solutions

Nonlinear two-point boundary-value problems (TPBVP) can be reduced to the iterative solution of a sequence of linear problems by means of quasilinearization techniques. Therefore, the efficient solution of linear problems is the key to the efficient solution of nonlinear problems.Among the techniques available for solving linear two-point boundary-value problems, the method of particular solutions (MPS) is particularly attractive in that it employs only one differential system, the original nonhomogeneous system, albeit with different initial conditions. This feature of MPS makes it ideally suitable for implementation on parallel computers in that the following requirements are met: the computational effort is subdivided into separate tasks (particular solutions) assigned to the different processors; the tasks have nearly the same size; there is little intercommunication between the tasks.For the TPBVP, the speedup achievable is ofO(n), wheren is the dimension of the state vector, hence relatively modest for the differential systems of interest in trajectory optimization and guidance. This being the case, we transform the TPBVP into a multi-point boundary-value problem (MPBVP) involvingm time subintervals, withm–1 continuity conditions imposed at the interface of contiguous subintervals. For the MPBVP, the speedup achievable is ofO(mn), hence substantially higher than that achievable for the TPBVP. It reduces toO(m) if the parallelism is implemented only in the time domain and not in the state domain.A drawback of the multi-point approach is that it requires the solution of a large linear algebraic system for the constants of the particular solutions. This drawback can be offset by exploiting the particular nature of the interface conditions: if the vector of constants for the first subinterval is known, the vector of constants for the subsequent subintervals can be obtained with linear transformations. Using decomposition techniques together with the discrete version of MPS, the size of the linear algebraic system for the multi-point case becomes the same as that for the two-point case.Numerical tests on the Intel iPSC/860 computer show that substantial speedup can be achieved via parallel algorithms vis-a-vis sequential algorithms. Therefore, the present technique has considerable interest for real-time trajectory optimization and guidance.Dedicated to the Memory of Professor Jan M. SkowronskiThis paper, based on Refs. 1–3, is a much condensed version of the material contained in these references.The technical assistance of the Research Center on Parallel Computation of Rice University, Houston, Texas is gratefully acknowledged.     

High resolution instrumentation system for fibre-Bragg grating aerospace sensors

A passive technique for high-resolution detection of the wavelength of peak reflection from fibre Bragg grating (FBG) sensors is presented. The approach, based on a de-convolution of the FBG spectrum and the spectrometer resolution, essentially overcomes the low spectral resolution (≈0.1 nm) associated with commercial spectrometers employing CCD detection. The performance of two algorithms, the Centroid Detection algorithm (CDA) and the least squares method (LSQ), are compared. The LSQ algorithm offers resolution enhancement of at least two orders of magnitude and is shown to be independent of the FBG intensity and bandwidth over a broad range.     

Buckley–James-type of estimators under the classical case cohort design

We consider the estimation problem with classical case-cohort data. The case-cohort design was first proposed by Prentice (Biometrics 73:1–11, 1986). Most studies focus on the Cox regression model. In this paper, we consider the linear regression model. We propose an estimator which extends the Buckley–James estimator to the classical case-cohort design. In order to derive the BJE, there is an additional problem of finding the generalized maximum likelihood estimator (GMLE) of the underlying distribution functions. We propose a self-consistent algorithm for the GMLE. We also justify that the GMLE is consistent and asymptotically normally distributed under certain regularity conditions. We further present some simulation results on the asymptotic properties of the BJE and apply our procedure to a data set used in the literature.