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对空间普通克里金插值方法在时间维度的扩展，既体现了数据间的空间相关性又体现了时间相关性(The extension of spatial ordinary Kriging interpolation method in time dimension embodies both spatial correlation and temporal correlation between data.)

说明：  使用ENVI IDL编程实现的交叉熵法阈值分割(Using IDL Programming to Realize Threshold Segmentation of Cross Entropy Method)

本书共分5章：第1章介绍GPU通用计算的发展历程，介绍并行计算的历史、现状以及面临的问题；第2章介绍CUDA的使用方法，帮助理解CUDA的编程模型、存储器模型和执行模型，掌握CUDA程序的编写方法；第3章探讨CUDA硬件架构，深入分析Tesla GPU架构与CUDA通用计算的相互作用：第4章总结CUDA的高级优化方法，对任务划分、存储器访问、指令流效率等课题进行探讨；第5章以丰富的实例展示如何使用CUDA的强大性能解决实际问题。(This book is divided into five chapters: Chapter 1 introduces the development process of general-purpose GPU computing, parallel computing introduces the history, current situation and problems Chapter 2 describes the use of CUDA to help understand the CUDA programming model, the memory model and implementation model, master CUDA program writing method Chapter 3 explores CUDA hardware architecture, in-depth analysis of Tesla GPU architecture and CUDA general-purpose computing interactions: Chapter 4 summarizes the CUDA advanced optimization methods, the division of tasks, memory access, instruction stream efficiency and other topics were discussed Chapter 5 with abundant examples show how to use CUDA strong performance to solve practical problems.)

粒子群算法优化机器手的运动轨迹参数，驱动机器手(Particle Swarm Optimization (PSO) algorithm optimizes the trajectory parameters of the manipulator to drive the manipulator)

说明：  裂纹是典型的线结构，在许多计算机视觉应用中都很有趣。在实际应用中，路面裂缝等许多裂缝连续性差、对比度低，给利用低层特征进行基于图像的裂缝检测带来了很大的挑战。在本文中，我们提出了深度裂纹——一个端到端可训练的深度卷积神经网络，通过学习用于裂纹表示的高级特征来自动检测裂纹。该方法将在层次卷积阶段学习到的多尺度深度卷积特征融合在一起，以获取线路结构。更详细的表示在大比例尺的feature maps中进行，更全面的表示在小比例尺的feature maps中进行。我们在SegNet的编码器解码器架构上构建深度裂纹网，并对在相同尺度下在编码器网络和解码器网络中生成的卷积特征进行配对融合。(Cracks are typical line structures that are of interest in many computer-vision applications. In practice, many cracks, e.g., pavement cracks, show poor continuity and low contrast, which bring great challenges to image-based crack detection by using low-level features. In this paper, we propose DeepCrack---an end-to-end trainable deep convolutional neural network for automatic crack detection by learning high-level features for crack representation. In this method, multi-scale deep convolutional features learned at hierarchical convolutional stages are fused together to capture the line structures. More detailed representations are made in larger scale feature maps and more holistic representations are made in smaller scale feature maps. We build DeepCrack net on the encoder decoder architecture of SegNet and pairwisely fuse the convolutional features generated in the encoder network and in the decoder network at the same scale.)

ASEM-51,組譯 單晶片組合語言程式 asem5113.zip解壓縮後，裡面有一堆檔案，可以不必安裝就能使用。(ASEM-51,group translation single chip combination language program)

计算机系统结构的一些幻灯片,适合学生参考-Computer system structure of slides, suitable for students

说明：  emditor强大的文本编辑工具， 有需要的可以下载(Emditor is a powerful text editing tool, which can be downloaded if necessary)

说明：  DCOOFDM系统仿真，非常好用的程序，值得推荐(DCOOFDM simulation test)

说明：  基于stm32l476的显示屏例程，接口为SPI，使用最新的HAL库，有cubemx工程文件可供参阅(Based on the display routine of stm32l476, the interface is SPI, using the latest HAL library, there are cubemx engineering files available for reference)