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ESRIMapObjectsLT 2 and MicrosoftVisual Basic6 to build an application that uses maps. Display a map with multiple layers. Control panning and zooming. Create a toolbar control. Base the display of map layers on scale. Perform spatial and logical queries. Display features with thematic renderers. Add vector data and images to a map programmatically.
標(biāo)簽： ESRIMapObjectsLT MicrosoftVisual application Display
上傳時(shí)間： 2013-12-18
上傳用戶：dbs012280
Abstract-In this paper, simple autonomous chaotic circuits coupled by resistors are investigated. By carrying out computer calculations and circuit experiments, irregular self-switching phenomenon of three spatial patterns characterized by the phase states of quasi-synchronization of chaos can be observed from only four simple chaotic circuits. This is the same phenomenon as chaotic wandering of spatial patterns observed very often from systems with a large number of degrees of freedom. Namely, one of spatial-temporal chaos observed from systems of large size can be also generated in the proposed system consisting of only four chaotic circuits. A six subcircuits case and a coupled chaotic circuits networks are also studied, and such systems are confirmed to produce more complicated spatio-temporal phenomena.
標(biāo)簽： investigated Abstract-In autonomous resistors
上傳時(shí)間： 2014-06-09
上傳用戶：h886166
Servlets and JavaServer Pages is the first complete guide to building dynamic Java-based Web applications using the new JavaServer Pages 2.0 and Servlets 2.4. Servlets and JavaServer Pages (JSP) provide a robust solution to developing large, complex Web applications, including multiserver projects. In addition to built-in security, portability, and a Web server, they offer developers the freedom to work with any operating system that supports Javabe it Linux, Windows, OSX, or Solaris. This authoritative book begins by explaining how to set up a Servlet and JSP development environment, including a discussion of containers, Java support, and installing and configuring Tomcat. The authors then thoroughly explore servlets and JSP, including significant coverage of custom tag libraries, newly available filters, and popular servlet and JSP design patterns. Readers can then test-drive the knowledge gained by constructing a book-support Web site.
標(biāo)簽： JavaServer Java-based Servlets complete
上傳時(shí)間： 2014-01-02
上傳用戶：zsjzc
This book is about writing TinyOS systems and applications in the nesC language. This chapter gives a brief overview of TinyOS and its intended uses. TinyOS is an open-source project which a large number of research universities and companies contribute to. The main TinyOS website, http://www.tinyos.net, has instructions for downloading and installing the TinyOS programming environment. The website has a great deal of useful information which this book doesn’t cover, such as common hardware platforms and how to install code on a node.
標(biāo)簽： This applications language chapter
上傳時(shí)間： 2017-09-04
上傳用戶：253189838
These codes require an ASCII input file interp.dat of the following form: N: Number of Polynomial Interpolation Points (Small) First Sample (x1,y1) Second Sample (x2,y2) ... Nth Sample (xN,yN) N1: Number of Error Evaluation Points (Large) First Sample (x1,y1) Second Sample (x2,y2) ... N1th Sample (xN1,yN1)
標(biāo)簽： Polynomia following require Number
上傳時(shí)間： 2017-09-21
上傳用戶：許小華
The object detector described below has been initially proposed by P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a Dalal-Triggs detector that uses a single filter on histogram of oriented gradients (HOG) features to represent an object category. This detector uses a sliding window approach, where a filter is applied at all positions and scales of an image. The first innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a “root” filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated deformation models. The score of one of star models at a particular position and scale within an image is the score of the root filter at the given location plus the sum over parts of the maximum, over placements of that part, of the part filter score on its location minus a deformation cost easuring the deviation of the part from its ideal location relative to the root. Both root and part filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of a feature pyramid computed from the input image. Another improvement is a representation of the class of models by a mixture of star models. The score of a mixture model at a particular position and scale is the maximum over components, of the score of that component model at the given location.
標(biāo)簽： 計(jì)算機(jī)視覺(jué)
上傳時(shí)間： 2015-03-15
上傳用戶：sb_zhang
Writing essays and dissertations can be a major concern for overseas students studying at English-medium colleges and universities. Virtually all courses contain a large degree of written assessment and it is essential to ensure that your writing skills meet the necessary standard. Academic Writing is a new kind of writing course for all international students who have to write exams or coursework in English. This practical book thoroughly explains the writing process and covers all the key writing skills.
標(biāo)簽： Academic writing
上傳時(shí)間： 2015-11-13
上傳用戶：blackbat
We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
標(biāo)簽： 傳感器網(wǎng)絡(luò)
上傳時(shí)間： 2016-11-27
上傳用戶：xxmluo
RANSAC 單模型估計(jì)算法。比較簡(jiǎn)單易懂，模型重構(gòu)的基礎(chǔ)算法，適合新手使用學(xué)習(xí)
標(biāo)簽： estimation RANSAC scale
上傳時(shí)間： 2017-03-09
上傳用戶：gankiceljw
virtex ultra scale plus 16nm vcu 188 board user guide. For high speed and ultra scale design prototype.
標(biāo)簽： xilinx guide user vcu 118
上傳時(shí)間： 2017-05-16
上傳用戶：hewangfeng
蟲(chóng)蟲(chóng)下載站版權(quán)所有 京ICP備2021023401號(hào)-1
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