megahal is the conversation Simulators conversing with a user in natural language. The program will exploit the fact that human beings tend to read much more meaning into what is said than is actually there MegaHAL differs from conversation Simulators such as ELIZA in that it uses a Markov Model to learn how to hold a conversation. It is possible to teach MegaHAL to talk about new topics, and in different languages.
标签： conversation conversing Simulators language
上传时间： 2015-10-09
上传用户：lnnn30
Agilent.ADS.Using Circuit Simulators[2004-09].pdf
标签： Simulators Agilent Circuit Using
上传时间： 2016-04-28
上传用户：天涯
In this program, several statistical fading channel Simulators using the Sum-of-Sinusoids (SoS)has been implemented.A Rayleigh fading channel impulse respose using jakes model has been generated in matlab
标签： Sum-of-Sinusoids statistical Simulators program
上传时间： 2017-05-30
上传用户：ainimao
In this first part of the book the Vienna Link Level (LL) Simulators are described. The first chapter provides basics of LL simulations, introduces the most common variables and parameters as well as the transceiver structures that are applied in Long-Term Evolution (LTE) and Long-Term Evolution-Advanced (LTEA). We focus here mostly on the Downlink (DL) of LTE as most results reported in later chapters are related to DL transmissions.
标签： LTE-Advanced Simulators Vienna
上传时间： 2020-06-01
上传用户：shancjb
Abstract: Alexander Graham Bell patented twisted pair wires in 1881. We still use them today because they work so well. In addition we have the advantage ofincredible computer power within our world. Circuit Simulators and filter design programs are available for little or no cost. We combine the twisted pair and lowpassfilters to produce spectacular rejection of radio frequency interference (RFI) and electromagnetic interference (EMI). We also illustrate use of a precision resistorarray to produce a customizable differential amplifier. The precision resistors set the gain and common mode rejection ratios, while we choose the frequencyresponse.
上传时间： 2014-11-26
上传用户：Vici
Abstract: Nonideal cable dispersive effects can affect system performance. This application note discusses the twomain loss effects related to cables (skin-effect and dielectric losses), and presents a simple method of modeling thecable for use in standard SPICE Simulators.
上传时间： 2014-11-17
上传用户：wxnumen
Tornado 的manuals 很全面,国内的书大部分是翻译的它。经常需要查阅的。Tornado Online Manuals GDB User s Guide GNU Make User s Guide GNU Toolchain Release Notes GNU Toolkit User s Guide for Pentium GNU Toolkit User s Guide for Simulators, 68K, and SH Tornado API Guide Tornado API Reference Tornado Getting Started Guide (Windows Version) Tornado Migration Guide Tornado Reference Tornado Release Notes Tornado SETUP SDK Developer s Guide Tornado User s Guide (Windows Version) USB Developer s Kit Programmer s Guide USB Developer s Kit Release Notes VxWorks API Reference VxWorks BSP Developer s Guide VxWorks BSP Developer s Reference VxWorks BSP Reference VxWorks Errno Code List VxWorks Network Programmer s Guide VxWorks Programmer s Guide VxWorks for Pentium Architecture Supplement WindView User s Guide WindView User s Reference
标签： Tornado Manuals manuals Online
上传时间： 2016-05-16
上传用户：13215175592
The NCTUns network simulator and emulator is developed at NCTU, Taiwan. Its predecessor is the Harvard network simulator (invented by Prof. S.Y. Wang in 1999). By using a novel simulation methodology, it can do several tasks that traditional network Simulators cannot easily do.
标签： predecessor developed simulator emulator
上传时间： 2014-12-01
上传用户：txfyddz
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
Modeling and simulation of nonlinear systems provide communication system designers with a tool to predict and verify overall system performance under nonlinearity and complex communication signals. Traditionally, RF system designers use deterministic signals (discrete tones), which can be implemented in circuit Simulators, to predict the performance of their nonlinear circuits/systems. However, RF system designers are usually faced with the problem of predicting system performance when the input to the system is real-world communication signals which have a random nature.
标签： Nonlinear_Distortion_in_Wireless_ Systems
上传时间： 2020-05-30
上传用户：shancjb
