介绍snoopy仿真软件的功能和使用。snoopy是一种功能全面的Petri网仿真和分析工具。
2021-11-20 13:02:13 837KB petri
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本书是算法设计畅销书的经典版本,是设计实用且高效算法的最全面指导书。本书揭密了算法的设计与分析,以简单易懂的写作风格,介绍了各种算法技术,着重强调了算法分析,全书包括两大部分,“技术”部分介绍了设计和分析计算机算法的各种方法,“资源”部分给出了大量的参考资源,以及算法实现的各种资源,此外,在作者的个人网址上还提供了各种教学资源和参考材料,这些资源对读者很有参考价值。. 本书可以作为算法设计课程的主教材,也是程序人员、研究人员和学生的常备参考书。
2021-11-20 07:45:03 3.13MB 算法设计手册 第二版
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雷达系统设计MATLAB仿真英文原版,字迹超级清晰。。
2021-11-19 21:49:41 33.52MB Matlab Simulations Radar Mahafza
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Design for Six Sigma (DFSS) offers engineers powerful opportunities to develop more successful systems, software, hardware, and processes. In Applying Design for Six Sigma to Software and Hardware Systems , two leading experts offer a realistic, step-by-step process for succeeding with DFSS. Their clear, start-to-finish roadmap is designed for successfully developing complex high-technology products and systems that require both software and hardware development. Drawing on their unsurpassed experience leading Six Sigma at Motorola, the authors cover the entire project lifecycle, from business case through scheduling, customer-driven requirements gathering through execution. They provide real-world examples for applying their techniques to software alone, hardware alone, and systems composed of both. Product developers will find proven job aids and specific guidance about what teams and team members need to do at every stage. Using this book’s integrated, systems approach, marketers, software professionals, and hardware developers can converge all their efforts on what really matters: addressing the customer’s true needs. Learn how to Ensure that your entire team shares a solid understanding of customer needs Define measurable critical parameters that reflect customer requirements Thoroughly assess business case risk and opportunity in the context of product roadmaps and portfolios Prioritize development decisions and scheduling in the face of resource constraints Flow critical parameters down to quantifiable, verifiable requirements for every sub-process, subsystem, and component Use predictive engineering and advanced optimization to build products that robustly handle variations in manufacturing and usage Verify system capabilities and reliability based on pilots or early production samples Master new statistical techniques for ensuring that supply chains deliver on time, with minimal inventory Choose the right DFSS tools, using the authors’ step-by-step flowc
2021-11-19 20:23:18 5.55MB Eric Maass DFSS
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Microwave solid state circuits are characterised by being etched on a suitable dielectric substrate. They are generically referred to as Microwave Integrated Circuits (MIC). This contributed volume presents a comprehensive discussion of the design of passive circuits, solid state devices, and microwave solid state circuits.
2021-11-19 10:44:59 47.29MB Microwave Circuit
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MEMS经典教材,所有MEMS工程师必备
2021-11-18 19:33:34 14.39MB MEMS
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非常经典的数字集成电路设计教材和参考 内容详实,结构清晰,涉及到设计IC的你所需要关注的方方面面 一书在手,无需再有
2021-11-18 17:14:27 12.46MB 数字集成电路
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此代码演示了使用灰狼优化技术在部分阴影条件下对光伏系统进行 MPPT 设计的 MATLAB 实现 参考: Mirjalili、Seyedali、Seyed Mohammad Mirjalili 和 Andrew Lewis。 “灰狼优化器。” 工程软件进展 69 (2014): 46-61。 Mohanty、Satyajit、Bidyadhar Subudhi 和 Pravat Kumar Ray。 “在部分遮阳条件下,针对光伏系统使用灰狼优化技术的新 MPPT 设计。” IEEE 可持续能源交易 7,没有。 1 (2015): 181-188 如有疑问,请联系: jkd.power.energy.solutions@gmail.com 优酷演示: https://youtu.be/SrwIGu6nthI 基于灰狼优化和扰动观察法的混合MPPT: https://youtu.be/
2021-11-18 16:39:40 34KB matlab
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Nerual Network Design (2nd Edition) Content Ch 2 Neuron Model and Network Architectures Ch 3 An Illustrative Example Ch 4 Perceptron Learning Rule Ch 5 Signal and Weight Vector Spaces Ch 6 Linear Transformations for Neural Networks Ch 7 Supervised Hebbian Learning Ch 8 Performance Surfaces and Optimum Points Ch 9 Performance Optimization Ch 10 Widrow-Hoff Learning Ch 11 Backpropagation Ch 12 Variations on Backpropagation Ch 13 Generalization Ch 14 Dynamic Networks Ch 15 Associative Learning Ch 16 Competitive Networks Ch 17 Radial Basis Networks Ch 18 Grossberg Network Ch 19 Adaptive Resonance Theory Ch 20 Stability Ch 21 Hopfield Network Ch 22 Practical Training Issues Ch 23 Case Study 1:Function Approximation Ch 24 Case Study 2:Probability Estimation Ch 25 Case Study 3:Pattern Recognition Ch 26 Case Study 4: Clustering Ch 27 Case Study 5: Prediction
2021-11-18 15:32:31 11.27MB Nerual Network Design; 2E
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