基于TMS320C6678的多核程序加载研究与实现

针对多核D SP系统程序加载复杂的问题,基于T MS320C6678对多核程序加载进行了研究与设计。从一级引导程序出发,设计并优化了多核程序内容存储格式。设计了简洁的二级引导程序,以修正一级引导程序只识别主核程序入口地址,而从核入口地址缺失的现象。为了快速生成特定格式的多核程序内容,设计了多个工具用于添加S PI启动参数表、DDR3启动表、从核程序入口地址以及完成程序内容格式的转换。实现了S PI Flash多核程序加载以及基于I2C主模式的Nand Flash多核程序加载。     

Efficient near-duplicate image detection with a local-based binary representation

Efficient near-duplicate image detection is important for several applications that feature extraction and matching need to be taken online. Most image representations targeting at conventional image retrieval problems are either computationally expensive to extract and match, or limited in robustness. Aiming at this problem, in this paper, we propose an effective and efficient local-based representation method to encode an image as a binary vector, which is called Local-based Binary Representation (LBR). Local regions are extracted densely from the image, and each region is converted to a simple and effective feature describing its texture. A statistical histogram can be calculated over all the local features, and then it is encoded to a binary vector as the holistic image representation. The proposed binary representation jointly utilizes the local region texture and global visual distribution of the image, based on which a similarity measure can be applied to detect near-duplicate image effectively. The binary encoding scheme can not only greatly speed up the online computation, but also reduce memory cost in real applications. In experiments the precision and recall, as well as computational time of the proposed method are compared with other state-of-the-art image representations and LBR shows clear advantages on online near-duplicate image detection and video keyframe detection tasks.     

图谱法脑部MRI图像自动分割技术发展及应用

脑部MRI图像自动分割是计算机技术运用于医学上的一个典 型工作,脑部图像分割技术对于人类研究脑部疾病具有重要意义。虽然有一些非常广泛应用 的图像分割方法,如阈值法、区域增长法、聚类法等,但在脑部MRI图像分割中,这些方法 都 没有图谱法具有更为实际的医学研究与临床价值。本文回顾了脑部图像配准、分割的发展历 程,介绍了图谱分割算法的发展及基本原理,以及当前比较前沿的多图谱分割系统的组成和 应用。最后本文对图谱法脑部自动分割在实际临床医学中的应用前景作了总结和展望。     

二维圆环结构中弹性波传播的谱单元分析

为研究弹性波在结构中的波场特征,推导建立一种任意四边形二维谱单元,将其应用于二维圆环结构中的波传播行为模拟.以矩形平板结构中弹性导波传播分析为例,通过与传统有限元分析结果对比,验证所建立谱单元的有效性.有裂纹和无裂纹二维圆环结构谱单元模拟结果表明:弹性波在圆环结构中传播会发生频散;圆环结构表面的裂纹对瑞利波的传播影响最大;根据其反射波包位置可以确定损伤位置.     

论包装色彩设计中的多维构架

文章从色彩因子在包装中的运用和色彩的不同属性入手,研究了包装色彩的释义及美学特征。进而从基础属性、支柱属性、以及高级属性等不同维度,阐述包装色彩设计的总体要求。从理论上论证了用多维构架思维进行包装色彩设计的合理性,为包装色彩设计提供了可以借鉴的思路。     

物联网中的信息安全与防范措施

随着信息化社会的不断发展,物联网以其广泛、便捷等特点备受关注。物联网的出现,为互联网的普及提供了一个良好的基础平台。物联网是继计算机、互联网之后又一信息化飞跃,将为信息化生活的加快带来极大的机遇与挑战。并且物联网共享的数据与人们的生活息息相关,这决定了物联网信息的广泛性和敏感性。对物联网中的信息安全和防范措施提出了更高的要求。     

A Balanced Approach to IT Transformation

The continuous improvement strategies necessary in today's climate of random change mandate that IT organizations transform the way they relate to other business units, deploy new technology, and organize and develop their people. Crafting an individualized transformation program that balances efforts in each of these areas will help IT managers add value to the bottom line while achieving real gains in customer service and productivity.     

Pulse-order recursive method for inverse covariance matrix computation applied to space-time adaptive processing

The conventional space-time adaptive processing(STAP) method such as the typical sample matrix inversion(SMI)-based STAP method is difficult to implement for a practical system because intense computational complexity arises in calculating the inversion of a space-time covariance matrix directly.According to the block Hermitian matrix property of space-time covariance matrix,a new pulse-order recursive method is proposed in this paper to calculate the inverse covariance matrix for the STAP adaptive weight,which can reduce the computational complexity significantly.The proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix property.In the following,the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance matrix.Next,the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously obtained.Compared with the conventional SMI-based STAP algorithms,the computational complexity of the proposed method is reduced to more than 50% for the same clutter suppression performance.This method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.