wireless tools: used to manipulate the Wireless Extensions. The Wireless Extensions is an interface allowing you to set Wireless LAN specific PARAMETERS and get the specific stats. It also contains the IfRename package, used for advance renaming of network interfaces. We have cross compile to arm linux. and fixed some bug (eg:sometime the essid will be rename to a long name, or sometime it will disaply the essid twice)
標簽： Extensions Wireless manipulate interface
上傳時間： 2014-11-26
上傳用戶：wlcaption
In the planning stage of a GNSS-measurement campaign it is useful to compute several design para-meters in order to decide how, when and where to carry out the measurements. The MATLAB user interface VISUAL.M enables you to compute the design PARAMETERS for any system design.
標簽： GNSS-measurement planning campaign para-met
上傳時間： 2014-01-23
上傳用戶：tuilp1a
The target of the assignment is to familiarize the student with MIMO channel modeling. The work is based on L. Schumacher’s MIMO channel model implementation, with added capacity analysis. First the channel model implementation is introduced, and thereafter analysis on MIMO channel with different PARAMETERS is done. Finally a short report on the results is written.
標簽： familiarize assignment The the
上傳時間： 2014-01-01
上傳用戶：jjj0202
It s an entire application that uses knowdledge of probabilistic and statistical math to generate and display radom variables characteristics and histograms...it includes a console too for changing or viewing general PARAMETERS in the form of commands sent to the application....Enjoy!
標簽： probabilistic application statistical knowdledge
上傳時間： 2014-01-01
上傳用戶：zhangliming420
A version of a sparse bundle adjustment implementation with adjustable intrinsics and distortion PARAMETERS (either shared by all views or varying for each view)
標簽： implementation adjustment adjustable distortion
上傳時間： 2017-09-09
上傳用戶：Andy123456
RF Amplifier Design：1. Active devices and S-PARAMETERS 2. Amplifier impedance matching technique 3. Power gain of amplifiers 4. Stability of RF amplifiers 5. Power gain circles of amplifiers 6. Bias networks of active devices 7. Small signal amplifier design example
標簽： 5g
上傳時間： 2015-02-14
上傳用戶：Coight
物理科學,Experimental investigation of the governing PARAMETERS in the
標簽： 紡絲
上傳時間： 2015-04-16
上傳用戶：灰原亞梨兒
ESPRIT-Estimation of Signal PARAMETERS V Rotational Invariance Techniques
標簽： ESPRIT-Estimation of Signal PARAMETERS V Rotational Invariance Techniques
上傳時間： 2015-04-30
上傳用戶：小楚88
AFCRL Atmospheric Absorption Line PARAMETERS Compilation
標簽： AFCRL Atmospheric Absorption Line PARAMETERS Compilation
上傳時間： 2016-03-30
上傳用戶：xilong1393
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system PARAMETERS, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system PARAMETERS in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標簽： Optimization and Uncertainty Quantification
上傳時間： 2016-04-08
上傳用戶：huhu123456
