资源列表
FormalFormalRequirementsforVirtualizableThirdGener
- 这是Gerald J. Popek在1974年发表的虚拟化奠基性论文Formal Requirements for Virtualizable Third Generation Architectures-Gerald J. Popek Formal Requirements for Virtualizable Third Generation Architectures ACM
LA
- Like so many electronic test and measurement tools, a logic analyzer is a solution to a particular class of problems. It is a versatile tool that can help you with digital hardware debug, design verification and embedded software debug. The log
COMPASS-and-GPS-position-
- 利用实验数据对beidou和GPS的定位性能进行了分析，得到北斗的定位性能稳定的结论-Using the experimental data and the GPS positioning beidou performance analysis, a stable positioning performance Beidou conclusions
filterdesign_and_hfss_ho
- 介绍了微波滤波器的设计流程以及腔体滤波器的设计方法-The design flow of microwave filter and the design method of cavity filter are introduced.
Dual-mode-research-for-microgrid
- 微网的双模式研究，对微电网逆变器的下垂控制、PQ控制以及孤岛检测方法进行了调研，对它们进行简要的叙述，文档作为课题的开题报告-Dual-mode research for microgrid
ArcIMStiles
- 基于 ArcIMS的地图切图原理(定范围) 此切图原理服务于基于预生成技术的Web地图显示系统，这种技术 在2006年已经广泛应用于公共地图服务领域，包括国内用户使用较多 的GoogleMaps、Microsoft Live Map、YahooMaps、51ditu、Mapbar、 SogouMap等；-ArcIMS-based map of the cut diagram (scope) This cutting diagram generated based on p
Translated_NRZ_DP_QPSK_112G_(11Abr2011_8AM)
- Resumo - Neste trabalho é apresentada uma transmissã o óptica experimental de 3,58 TB/s utilizando 32 canais modulados a 112 Gb/s com o uso do formato de modulaç ã o NRZ-DP-QPSK e detecç ã o coerente. Os efeitos da filtragem óptic
Smal-l-Target--Detection
- 提出了一种新的基于小波包变换 和偏斜度的检测方法。该方法利用小波包对图像进行多尺度分解，解决了高频段分辨率低的问题； 并提出了一个基于偏斜度的高斯判别准则，用于对小波包分解系数进行高斯性检验，最终得到了 小目标的精确检测-The wavelet packets were applied to decompose the image into pyramid subbands at different scales and solve the problem of the high
assembly_language_toolsTMS470R1x
- assembly level optimsing for DSP
FLUENT---Tutorial---Dynamic-mesh---Missile-Silo-L
- dynamic meshing of a missile body
n3_001.pdf
- tutorial for NS2 learning.easy and learning.
Improved-Feature-Extraction-algorithm-Using-WDT.r
- wavelet transform in speech recognition will be briefly reviewed. we describe how the features are extracted, different algorithm, weighting will be introduced-wavelet transform in speech recognition will be briefly reviewed. we describe h