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
标签： Optimization and Uncertainty Quantification
上传时间： 2016-04-08
上传用户：huhu123456
音频传输FPGA代码。。。。。。。。。咋这个规则这么多麻烦
标签： fpga-coding
上传时间： 2016-05-15
上传用户：DKCJ02
This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
标签： Microphone array Tutorial Array Signal Processing
上传时间： 2016-06-12
上传用户：halias
32feet.NET is a shared-source project to make personal area networking technologies such as Bluetooth, Infrared (IrDA) and more, easily accessible from .NET code. Supports desktop, mobile or embedded systems. 32feet.NET is free for commercial or non-commercial use. If you use the binaries you can just use the library as-is, if you make modifications to the source you need to include the 32feet.NET License.txt document and ensure the file headers are not modified/removed. The project currently consists of the following libraries:- Bluetooth IrDA Object Exchange Bluetooth support requires a device with either the Microsoft, Widcomm, BlueSoleil, or Stonestreet One Bluetopia Bluetooth stack. Requires .NET Compact Framework v3.5 or above and Windows CE.NET 4.2 or above, or .NET Framework v3.5 for desktop Windows XP, Vista, 7 and 8. A subset of functionality is available for Windows Phone 8 and Windows Embedded Handheld 8 in the InTheHand.Phone.Bluetooth.dll library.
上传时间： 2016-07-06
上传用户：magister2016
asp实现限制一个ip只能访问一次的方法 <% '///////////////////////////////////////////////////// '// // '//作用：一个IP地址只允许访问本页一次 // '//引用：<!-- #include file="Check_Ip.asp" --> // '// // '///////////////////////////////////////////////////// 'Response.Charset = 936 '设置输出编码为简体中文 'Response.Buffer = false '关闭缓冲区 Dim Fso,ts,IpList,Cfs '设置Cookies函数 Function SetCookie() Response.Cookies("IsBrow") = "Brow" Response.Cookies("IsBrow").Expires = Date+365 End Function '记录IP地址函数 Function WriteIp(FileName, IpAddress) Set Fso = Server.CreateObject("Scripting.FileSystemObject") Set ts = Fso.OpenTextFile(Server.MapPath(FileName),8,true) ts.WriteLine IpAddress ts.Close Set ts = Nothing Set Fso = Nothing End Function '读取IP地址函数 Function ReadIpList(FileName) Set Fso = Server.CreateObject("Scripting.FileSystemObject") If Not Fso.FileExists(Server.MapPath(FileName)) Then CreateFile("Iplist.txt") Exit Function End If Set ts = Fso.OpenTextFile(Server.MapPath(FileName)) Iplist = ts.ReadAll ts.Close Set ts = Nothing Set Fso = Nothing ReadIpList = Iplist End Function '创建文件函数 Function CreateFile(FileName) Set Fso = Server.CreateObject("Scripting.FileSystemObject") Set Cfs = Fso.CreateTextFile(Server.MapPath(FileName)) Cfs.Close Set Cfs = Nothing Set Fso = Nothing End Function '关闭当前IE窗口函数(注:IE6下通过,其他浏览器未测试) Function CloseWindow() 'Response.Write "<script>window.location='javascript:window.opener=null;window.close();'</script>" Response.Redirect "http://www.baidu.com" End Function Ip = Request.ServerVariables("REMOTE_ADDR") '获取浏览者IP地址 Cookie = Request.Cookies("IsBrow") '获取当前Cookies 'Response.Write Cookie If Request.ServerVariables("HTTP_X_FORWARDED_FOR") <> "" Then Response.Write "本站不允许使用代理访问" Response.End() Else If Cookie = "Brow" Then CloseWindow() Else If Instr(ReadIpList("Iplist.txt"),Ip) <>0 Then CloseWindow() Else WriteIp "Iplist.txt" , Ip End If SetCookie() End If End If %>
上传时间： 2016-07-14
上传用户：helei0915
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.
标签： 传感器网络
上传时间： 2016-11-27
上传用户：xxmluo
一本难得得关于通信纠错码得好书。对原文件进行了优化----添加了目录，链接，大大缩小了体积。
标签： mathmatical Correction algorithms Coding method Error and
上传时间： 2017-10-08
上传用户：jinnmy
The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.
标签： frequency-domain interpolation performance Design kbit_s speech coder based and of
上传时间： 2018-04-08
上传用户：kilohorse
Abstract—In the future communication applications, users may obtain their messages that have different importance levels distributively from several available sources, such as distributed storage or even devices belonging to other users. This scenario is the best modeled by the multilevel diversity coding systems (MDCS). To achieve perfect (information-theoretic) secrecy against wiretap channels, this paper investigates the fundamental limits on the secure rate region of the asymmetric MDCS (AMDCS), which include the symmetric case as a special case. Threshold perfect secrecy is added to the AMDCS model. The eavesdropper may have access to any one but not more than one subset of the channels but know nothing about the sources, as long as the size of the subset is not above the security level. The question of whether superposition (source separation) coding is optimal for such an AMDCS with threshold perfect secrecy is answered. A class of secure AMDCS (S-AMDCS) with an arbitrary number of encoders is solved, and it is shown that linear codes are optimal for this class of instances. However, in contrast with the secure symmetric MDCS, superposition is shown to be not optimal for S-AMDCS in general. In addition, necessary conditions on the existence of a secrecy key are determined as a design guideline.
标签： Fundamental Limits Secure Class on of
上传时间： 2020-01-04
上传用户：kddlas
Mobile communication devices like smart phones or tablet PCs enable us to consume information at every location and at every time. The rapid development of new applications and new services and the demand to access data in real time create an increasing throughput demand. The data have to be transmitted reliably to ensure the desired quality of service. Furthermore, an improved utilization of the bandwidth is desired to reduce the cost of transmission.
标签： Architectures Processing Baseband Signal for
上传时间： 2020-05-26
上传用户：shancjb
