Search Results - (((((((ant OR wantii) OR mantic) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

Understanding smart sensors by Frank, Randy

Table of Contents: “…ZigBee-Like Wireless -- 8.3.3. ANT+ -- 8.3.4.6LoWPAN -- 8.3.5. Near Field Communication (NFC) -- 8.3.6.Z-Wave -- 8.3.7. …”
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Fundamentals of Fluid Power Control. by Watton, John

Table of Contents: “…Control-Volume Flow Continuity -- PRV Flow -- Force Balance at the Spindle -- 5.13.3 Frequency Response from a Linearized Transfer Function Analysis -- 5.14 Servovalve Dynamics -- First-Stage, Armature, and Flapper-Nozzle -- Flapper-Nozzle and Resistance Bridge Flow Characteristic -- Force Balance at the Spool -- 5.15 An Open-Loop Servovalve-Motor Drive with Line Dynamics Modeled by Lumped Approximations -- Servovalve, Dynamics Included, Underlapped Spool -- Lines, Laminar Mean Flow, Two Lump Approximations per Line, Negligible Motor Internal Volume -- Motor Flow and Torque Equations -- 5.16 Transmission Line Dynamics -- 5.16.1 Introduction -- Servovalve-Cylinder with Short Lines and Significant Actuator Volumes -- Servovalve-Motor with Long Lines and Negligible Actuator Volumes -- 5.16.2 Lossless Line Model for Z and Y -- 5.16.3 Average and Distributed Line Friction Models for Z and Y -- 5.16.4 Frequency-Domain Analysis -- 5.16.5 Servovalve-Reflected Linearized Coefficients -- 5.16.6 Modeling Systems with Nonlossless Transmission Lines, the Modal Analysis Method -- 5.16.7 Modal Analysis Applied to a Servovalve-Motor Open-Loop Drive -- 5.17 The State-Space Method for Linear Systems Modeling -- 5.17.1 Modeling Principles -- 5.17.2 Some Further Aspects of the Time-Domain Solution -- 5.17.3 The Transfer Function Concept in State Space -- 5.18 Data-Based Dynamic Modeling -- 5.18.1 Introduction -- 5.18.2 Time-Series Modeling -- 5.18.3 The Group Method of Data Handling (GMDH) Algorithm -- 5.18.4 Artificial Neural Networks -- 5.18.5 A Comparison of Time-Series, GMDH, and ANN Modeling of a Second-Order Dynamic System -- 5.18.6 Time-Series Modeling of a Position Control System -- 5.18.7 Time-Series Modeling for Fault Diagnosis -- 5.18.8 Time-Series Modeling of a Proportional PRV -- 5.18.9 GMDH Modeling of a Nitrogen-Filled Accumulator.…”
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Flood hazard identification and mitigation in semi- and arid environments

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Sigma-Delta Converters. by De la Rosa, José M.

Table of Contents: “…4.5.2 Effect of Finite Slew Rate on CT-Ms 133 -- 4.6 Sources of Distortion in CT-Ms 134 -- 4.6.1 Nonlinearities in the Front-end Integrator 134 -- 4.6.2 Intersymbol Interference in the Feedback DAC 136 -- 4.7 Circuit Noise in CT-Ms 137 -- 4.7.1 Noise Analysis Considering NRZ Feedback DACs 137 -- 4.7.2 Noise Analysis Considering SC Feedback DACs 139 -- 4.8 Clock Jitter in CT-Ms 140 -- 4.8.1 Jitter in Return-to-zero DACs 141 -- 4.8.2 Jitter in Non-return-to-zero DACs 142 -- 4.8.3 Jitter in Switched-capacitor DACs 144 -- 4.8.4 Lingering Effect of Clock Jitter Error 145 -- 4.8.5 Reducing the Effect of Clock Jitter with FIR and Sine-shaped DACs 147 -- 4.9 Excess Loop Delay in CT-Ms 149 -- 4.9.1 Intuitive Analysis of ELD 149 -- 4.9.2 Analysis of ELD based on Impulse-invariant DT-CT Transformation 151 -- 4.9.3 Alternative ELD Compensation Techniques 154 -- 4.10 Quantizer Metastability in CT-Ms 155 -- 4.11 Summary 159 -- References 160 -- 5 Behavioral Modeling and High-level Simulation 165 -- 5.1 Systematic Design Methodology of Modulators 165 -- 5.1.1 System Partitioning and Abstraction Levels 167 -- 5.1.2 Sizing Process 167 -- 5.2 Simulation Approaches for the High-level Evaluation of Ms 169 -- 5.2.1 Alternatives to Transistor-level Simulation 169 -- 5.2.2 Event-driven Behavioral Simulation Technique 171 -- 5.2.3 Programming Languages and Behavioral Modeling Platforms 172 -- 5.3 Implementing M Behavioral Models 173 -- 5.3.1 From Circuit Analysis to Computational Algorithms 173 -- 5.3.2 Time-domain versus Frequency-domain Behavioral Models 175 -- 5.3.3 Implementing Time-domain Behavioral Models in MATLAB 178 -- 5.3.4 Building Time-domain Behavioral Models as SIMULINK C-MEX S-functions 182 -- 5.4 Efficient Behavioral Modeling of M Building Blocks using C-MEX S-functions 188 -- 5.4.1 Modeling of SC Integrators using S-functions 188 -- 5.4.1.1 Capacitor Mismatch and Nonlinearity 190.…”
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Computational fluid-structure interaction : methods and applications by Bazilevs, Yuri

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Statistics for business by Mariappan, Perumal

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Polymer extrusion

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Disobedient Aesthetics : Surveillance, Bodies, Control by Stagliano, Anthony, 1973-

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Qualitative computing : a computational journey into nonlinearity by Chaitin-Chatelin, Françoise

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Visual Inspection Technology in the Hard Disc Drive Industry. by Muneesawang, Paisarn

Table of Contents: “…Introduction / Suchart Yammen / Paisarn Muneesawang -- 1.2. Algorithm for corrosion detection / Suchart Yammen / Paisarn Muneesawang -- 1.2.1. …”
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Formal languages, automata and numeration systems. 1, Introduction to combinatorics on words by Rigo, Michel

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Public safety networks from LTE to 5G by Yarali, Abdulrahman

Table of Contents: “…9.2.5 Flexibility 164 -- 9.3 Starting Public Safety Implementation Versus Waiting for 5G 165 -- 9.4 5GVersus 4G Public Safety Services 166 -- 9.4.1 Video Surveillance 167 -- 9.4.2 Computer-Driven Augmented Reality (AR) Helmet 167 -- 9.5 How 5GWill Shape Emergency Services 167 -- 9.6 4G LTE Defined Public Safety Content in 5G 168 -- 9.7 The Linkage Between 4G-5G Evolution and the Spectrum for Public Safety 168 -- 9.8 Conclusion 168 -- References 168 -- 10 Fifth Generation (5G) Cellular Technology 171 -- 10.1 Introduction 171 -- 10.2 Background Information on Cellular Network Generations 172 -- 10.2.1 Evolution of Mobile Technologies 172 -- 10.2.1.1 First Generation (1G) 172 -- 10.2.1.2 Second Generation (2G) Mobile Network 172 -- 10.2.1.3 Third Generation (3G) Mobile Network 172 -- 10.2.1.4 Fourth Generation (4G) Mobile Network 173 -- 10.2.1.5 Fifth Generation (5G) 173 -- 10.3 Fifth Generation (5G) and the Network of Tomorrow 174 -- 10.3.1 5G Network Architecture 176 -- 10.3.2 Wireless Communication Technologies for 5G 177 -- 10.3.2.1 Massive MIMO 177 -- 10.3.2.2 Spatial Modulation 179 -- 10.3.2.3 Machine to Machine Communication (M2M) 179 -- 10.3.2.4 Visible Light Communication (VLC) 180 -- 10.3.2.5 Green Communications 180 -- 10.3.3 5G System Environment 180 -- 10.3.4 Devices Used in 5G Technology 181 -- 10.3.5 Market Standardization and Adoption of 5G Technology 181 -- 10.3.6 Security Standardization of Cloud Applications 183 -- 10.3.7 The Global ICT Standardization Forum for India (GISFI) 184 -- 10.3.8 Energy Efficiency Enhancements 184 -- 10.3.9 Virtualization in the 5G Cellular Network 185 -- 10.3.10 Key Issues in the Development Process 185 -- 10.3.10.1 Challenges of Heterogeneous Networks 186 -- 10.3.10.2 Challenges Caused by Massive MIMO Technology 186 -- 10.3.10.3 Big Data Problem 186 -- 10.3.10.4 Shared Spectrum 186 -- 10.4 Conclusion 187 -- References 187 -- 11 Issues and Challenges of 4G and 5G for PS 189 -- 11.1 Introduction 189 -- 11.2 4G and 5GWireless Connections 190.…”
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Spread spectrum systems for GNSS and wireless communications by Holmes, Jack K. (Jack Kenneth), 1936-

Table of Contents: “…4.3.1 Convolutional Code Encoder Characterization -- 4.3.2 The Transfer Function of a Convolutional Code and the Free Distance -- 4.3.3 Decoding of Convolutional Codes -- 4.3.4 The Viterbi Algorithm -- 4.3.5 Error Probabilities for Viterbi Decoding of Convolutional Codes -- 4.3.6 Sequential Decoding of Convolutional Codes -- 4.3.7 Threshold Decoding of Convolutional Codes -- 4.3.8 Nonbinary Convolutional Codes -- 4.4 ITERATIVELY DECODED CODES -- 4.4.1 Turbo Codes -- 4.4.2 A Serial Concatenated Convolutional Code -- 4.4.3 Serial Concatenated Block Codes -- 4.4.4 Parallel Concatenated Block Codes -- 4.4.5 Low-Density Parity Check Codes -- 4.5 SELECTED RESULTS FOR SOME ERROR CORRECTION CODES -- 4.5.1 Bose, Chaudhuri, and Hocquenghem Codes -- 4.5.2 Reed-Solomon Codes -- 4.5.3 Convolutional Codes with Maximum Free Distance -- 4.5.4 Hard- and Soft-Decision FFH/MFSK with Repeat Coding BER Performance -- 4.6 SHANNON'S CAPACITY THEOREM, THE CHANNEL CODING THEOREM, AND BANDWIDTH EFFICIENCY -- 4.6.1 Shannon's Capacity Theorem -- 4.6.2 Channel Coding Theorem -- 4.6.3 Bandwidth Efficiency -- 4.7 APPLICATIONS OF ERROR CONTROL CODING -- 4.8 SUMMARY -- References -- Selected Bibliography -- Problems -- CHAPTER 5 Carrier Tracking Loops and Frequency Synthesizers -- 5.0 INTRODUCTION -- 5.1 TRACKING OF RESIDUAL CARRIER SIGNALS -- 5.2 PLL FOR TRACKING A RESIDUAL CARRIER COMPONENT -- 5.2.1 The Likelihood Function for Phase Estimation -- 5.2.2 The Maximum-Likelihood Estimation of Carrier Phase -- 5.2.3 Long Loops and Short Loops -- 5.2.4 The Stochastic Differential Equation of Operation -- 5.2.5 The Linear Model of the PLL with Noise -- 5.2.6 The Various Loop Filter Types -- 5.2.7 Transient Response of a Second-Order Loop -- 5.2.8 Steady State Tracking Error When the Phase Error Is Small -- 5.2.9 The Variance of the Linearized PLL Phase Error Due to Thermal Noise.…”
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Liquid surfaces and interfaces : synchrotron X-ray methods by Pershan, Peter S., 1934-

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IBM TotalStorage : SAN product, design, and optimization guide

Table of Contents: “…-- 3.7.6 What happens when there is more than one shortest path? -- 3.7.7 Can FSPF cause any problems? …”
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Optimal learning by Powell, Warren B., 1955-

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Queer Data Studies. by Keilty, Patrick

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Pink 2.0 : encoding queer cinema on the internet by Tsika, Noah, 1983-

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Primary surplus behavior and risks to fiscal sustainability in emerging market countries : a "fan-chart" approach by Celasun, Oya, Debrun, Xavier, Ostry, Jonathan D. (Jonathan David), 1962-

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Power system monitoring and control by Bevrani, Hassan

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