CXFTV2: A Fortran subroutine for the discrete least squares convex approximation

A Fortan subroutine calculates the least squares approximation to n data values containing random errors subject to non-negative second divided differences (convexity). The method employs a dual active set quadratic programming technique that allows several concavities of an iterate to be corrected simultaneously, which is a distinctive feature of this calculation. A B-spline representation of the iterates reduces each active set calculation to an unconstrained minimization with fewer variables that requires only O(n) computer operations. Details in these techniques including the data structure that establishes the implementation of the method are specified. Numerical testing on a variety of data sets indicates that the subroutine is particularly efficient, terminating after a small number of active set changes, the subroutine being suitable for large numbers of data. A numerical example and its output is provided to help the use of the software.     

基于混合参数蚁群算法的移动机器人路径规划北大核心

针对传统蚁群算法因初期信息素分布不均导致算法初期路径选择概率随机性大、搜索速度慢等缺陷,设计一种使用混合参数的蚁群改进算法。在算法开始阶段引入遗传算法,对遗传算法的适应度函数进行改进;设置一个评价点使遗传算法在合适的时机进入蚁群算法,并对算法的信息素挥发因子p采用一种自适应调整方式;对遗传算法的交叉率和变异率以及蚁群算法的信息因子和期望因子采用变异的混合参数,发挥4个参数因子在算法中的优点;在蚁群算法后面设置一个路径进化率的评价点判定是否再次进行遗传变异操作,目的是使蚁群算法跳出局部最优;算法最后引入B样条曲线光滑机制。实验结果表明:改进算法在简单和复杂的环境里找到的路径长度和路径拐点数明显减少,有比其他3种算法更快更准的寻找全局最优能力。     

Segmentation of historical machine-printed documents using Adaptive Run Length Smoothing and skeleton segmentation paths

In this paper, we strive towards the development of efficient techniques in order to segment document pages resulting from the digitization of historical machine-printed sources. This kind of documents often suffer from low quality and local skew, several degradations due to the old printing matrix quality or ink diffusion, and exhibit complex and dense layout. To face these problems, we introduce the following innovative aspects: (i) use of a novel Adaptive Run Length Smoothing Algorithm (ARLSA) in order to face the problem of complex and dense document layout, (ii) detection of noisy areas and punctuation marks that are usual in historical machine-printed documents, (iii) detection of possible obstacles formed from background areas in order to separate neighboring text columns or text lines, and (iv) use of skeleton segmentation paths in order to isolate possible connected characters. Comparative experiments using several historical machine-printed documents prove the efficiency of the proposed technique.     

基于三次指数平滑法的集装箱吞吐量预测

本文通过对宁波港历年来集装箱吞吐量的观察,发现其吞吐量呈持续性的曲线增长,因此采用三次指数平滑法对宁波港今后几年的集装箱吞吐量进行了预测。     

基于微分平滑滤波的特征点跟踪

光流跟踪作为一种重要的二维运动估计技术,在运动目标检测和跟踪中有着重要的作用.L-K光流跟踪算法是一种利用Newton-Raphson梯度下降法进行图像匹配的算法,所以离散图像的偏导数的计算显得尤为重要.由于数字图像离散的方格结构导致在计算各阶偏导数时产生较大的误差.利用微分平滑滤波的方法先利用一个连续的基础函数模拟离...     

Scale‐aware Structure‐Preserving Texture Filtering

This paper presents a novel method to enhance the performance of structure‐preserving image and texture filtering. With conventional edge‐aware filters, it is often challenging to handle images of high complexity where features of multiple scales coexist. In particular, it is not always easy to find the right balance between removing unimportant details and protecting important features when they come in multiple sizes, shapes, and contrasts. Unlike previous approaches, we address this issue from the perspective of adaptive kernel scales. Relying on patch‐based statistics, our method identifies texture from structure and also finds an optimal per‐pixel smoothing scale. We show that the proposed mechanism helps achieve enhanced image/texture filtering performance in terms of protecting the prominent geometric structures in the image, such as edges and corners, and keeping them sharp even after significant smoothing of the original signal.     

基于Nios的聚类向量ARMA轴温探测器——列车轴温探测系统的信号处理

阐述了在向量ARMA(AutoRegressive Moving Average,自回归滑动平均)模型中的聚类算法,介绍了使用Altera DSP Builder和SOPC Builder实现聚类向量自回归滑动平均的卡尔曼最优平滑滤波器的设计方法,给出了聚类向量ARMA卡尔曼最优平滑滤波器的设计框图,比较了32阶FIR（Finite Impulse Response ,有限冲击响应）滤波器与聚类向量ARMA卡尔曼最优平滑滤波器的滤波效果,同时还利用16阶DITFFT（时间抽取快速Fourier变换）展     

自适应单指数平滑法在短期交通流预测中的应用

短时交通流预测是实现交通规划和管理的关键技术之一. 指数平滑法因其计算过程简单, 需要观测数据较少等优点, 在短时交通流预测中获得了广泛的应用, 但其平滑系数缺乏有效的选取方法. 本文提出了一种自适应单指数平滑法, 通过近似动态规划方法的引入, 结合实际交通流数据对指数平滑系数进行优化, 使其随预测过程自动更新, 从而保证了预测的实时性、准确性. 严格的理论推导证明了这种预测方法的收敛性, 仿真结果验证了算法的有效性.     

低通平滑滤波对网络流量自相似性质的影响

从Hurst参数的小波估计方法出发,介绍了平滑滤波后的网络基础(低频)流量和原始流量在自相似性质的上表现规律,探讨了低通平滑滤波对流量自相似性质的影响。     

一种面积守恒的曲线平滑

传统意义上的曲线平滑是光滑曲线使之成为一段连续光滑的孤，但这是有收缩的。本文提出一种新的曲线平滑方法，这种方法不但具有传统平滑的效果，而且能使封闭曲线的面积在平滑后保持不变，因此这是无收缩的，从而更加合理。