scale Invariant algorithm
上傳時間： 2014-01-03
上傳用戶：003030
為了克服傳統的局部特征匹配算法對噪聲和圖像灰度非線性變換敏感的不足，提出了基于SIFT（Scale Invariant Feature Transform）描述算子的特征匹配算法。該算法首先
上傳時間： 2013-04-24
上傳用戶：hphh
Agilent AN 154 S-Parameter Design Application Note S參數的設計與應用 The need for new high-frequency, solid-state circuitdesign techniques has been recognized both by microwaveengineers and circuit designers. These engineersare being asked to design solid state circuitsthat will operate at higher and higher frequencies.The development of microwave transistors andAgilent Technologies’ network analysis instrumentationsystems that permit complete network characterizationin the microwave frequency rangehave greatly assisted these engineers in their work.The Agilent Microwave Division’s lab staff hasdeveloped a high frequency circuit design seminarto assist their counterparts in R&D labs throughoutthe world. This seminar has been presentedin a number of locations in the United States andEurope.From the experience gained in presenting this originalseminar, we have developed a four-part videotape, S-Parameter Design Seminar. While the technologyof high frequency circuit design is everchanging, the concepts upon which this technologyhas been built are relatively Invariant.The content of the S-Parameter Design Seminar isas follows:
標簽： S參數
上傳時間： 2013-12-19
上傳用戶：aa54
Semiconductor memory, card readers, microprocessors,disc drives, piezoelectric devices and digitally based systemsfurnish transient loads that a voltage regulator mustservice. Ideally, regulator output is Invariant during a loadtransient. In practice, some variation is encountered andbecomes problematic if allowable operating voltage tolerancesare exceeded. This mandates testing the regulatorand its associated support components to verify desiredperformance under transient loading conditions. Variousmethods are employable to generate transient loads, allowingobservation of regulator response
上傳時間： 2013-11-21
上傳用戶：semi1981
Copyright© 2004 Sergiu Dumitriu, Marta Gî rdea, Că tă lin Hriţ cu Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License" All brand names, product names, or trademarks belong to their respective holders.
標簽： Permission Copyright 259 Dumitriu
上傳時間： 2015-04-02
上傳用戶：jackgao
This paper addresses the issues relating to the enforcement of robust stability when implementing the Adaptive Inverse Control (AIC) scheme. In this scheme, an adaptive FIR filter is added to a closed-loop system in order to reduce the output error caused by external disturbances, enhancing the performance achieved by linear time-Invariant controllers alone.
標簽： implementing enforcement addresses the
上傳時間： 2013-12-23
上傳用戶：佳期如夢
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-Invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
標簽： identification considered features separati
上傳時間： 2016-09-20
上傳用戶：FreeSky
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.1 or any later version published by the Free Software Foundation with no Invariant Sections, with no Front- Cover Texts, and with no Back-Cover Texts. A copy of the license is included in the section entitled “GNU Free Documentation License”.
標簽： Permission distribute the document
上傳時間： 2016-11-30
上傳用戶：lxm
The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: (1) It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half, (2) The double-density DWT is overcomplete by a factor of two, and (3) It is nearly shift-Invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising however, there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions.
標簽： double-density improvement additional critically
上傳時間： 2017-04-03
上傳用戶：dongbaobao
