Search Results - ("algorithm" OR "algorithms")

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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Cybersecurity Law, standards and regulations by Schreider, Tari

Table of Contents: “…Authors of original encryption algorithms never really thought that governments would want to have access to their en... -- In an effort to bring sanity to the uncontrolled growth of encryption regulations, two important laws have been introduced. …”
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ARM system developer's guide : designing and optimizing system software by Sloss, Andrew N.

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Holland-Frei cancer medicine

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Introduction to Infrared and Electro-Optical Systems by Driggers, Ronald G.

Table of Contents: “…9.2 Conversion of Spatial and Temporal Frequencies -- 9.3 Electronics Transfer Function -- 9.4 Noise -- 9.4.1 Johnson Noise -- 9.4.2 1/f Noise -- 9.4.3 Shot Noise -- 9.5 MTF Boost Filter -- 9.6 Digital Filter MTF -- 9.7 CCDs -- 9.8 Uniformity Correction or NUC -- 9.9 Design and Construction of Camera Electronics -- References -- Chapter 10 Image Processing -- 10.1 Basics of Sampling Theory -- 10.2 Applications of Image Filtering -- 10.2.1 Localized Contrast Enhancement -- 10.2.2 Boost Filtering -- 10.2.3 Sensor Design Considerations -- 10.3 Super-Resolution Image Reconstruction -- 10.3.1 Image Acquisition: Microdither Scanner Versus Natural Jitter -- 10.3.2 Subpixel Shift Estimation -- 10.3.3 Image Reconstruction -- 10.3.4 Example and Performance Estimates -- 10.4 Image Fusion -- 10.4.1 Fusion Algorithms -- 10.5 Scene-Based NUC -- 10.6 Deep Learning -- 10.6.1 Super-Resolution -- 10.6.2 Contrast Enhancement -- 10.6.3 Image Fusion -- 10.6.4 Scene-Based NUC -- 10.7 Summary -- References -- Chapter 11 Displays, Human Perception, and Automatic Target Recognizers -- 11.1 Displays -- 11.2 CRTs -- 11.2.1 CRT Example Results -- 11.3 LEDs -- 11.4 LCDs -- 11.5 Plasma Displays -- 11.6 Emerging Display Technologies -- 11.7 Sampling and Display Processing -- 11.8 Human Perception and the Human Eye -- 11.9 MTF of the Eye -- 11.10 CTF of the Eye -- 11.11 Automatic Target Recognition -- References -- Chapter 12 Historical Performance Models -- 12.1 Introduction -- 12.2 Johnson Model Fundamentals -- 12.3 The MRT Model -- 12.4 The First FLIRs and Models -- 12.5 Model Improvements for Resolution and Noise -- 12.6 Incorporating Eye Contrast Limitations -- 12.7 Model Improvement to Add Sampling -- 12.8 Other Improvements Prior to the TTP Metric -- 12.9 The TRM3 Model -- 12.10 Triangle Orientation Discrimination (TOD).…”
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The 5-minute sports medicine consult

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Acoustical imaging : techniques and applications for engineers by Gan, Woon Siong

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XML for DB2 information integration

Table of Contents: “…-- 3.4 Creating an XML schema from a database schema -- 3.4.1 The algorithm.…”
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Statistical analysis in forensic science : evidential value of multivariate physicochemical data

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

Table of Contents: “…6.3.1 Hardware Emulation of CT-Ms on an FPGA 257 -- 6.3.2 GPU-accelerated Computing of CT-Ms 258 -- 6.4 Using Multi-objective Evolutionary Algorithms to Optimize Ms 259 -- 6.4.1 Combining MOEA with SIMSIDES 261 -- 6.4.2 Applying MOEA and SIMSIDES to the Synthesis of CT-Ms 262 -- 6.5 Summary 269 -- References 269 -- 7 Electrical Design of ??…”
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IBM TotalStorage Enterprise Storage Server model 800

Table of Contents: “…Performance -- 5.1 Performance accelerators -- 5.2 Third-generation hardware -- 5.3 RISC SMP processors -- 5.4 Caching algorithms -- 5.4.1 Optimized cache usage -- 5.4.2 Sequential pre-fetch I/O requests -- 5.5 Efficient I/O operations -- 5.5.1 SCSI command tag queuing -- 5.5.2 z/OS enhanced CCWs -- 5.6 Back-end high performance design -- 5.6.1 Serial Storage Architecture (SSA) -- 5.6.2 Striping -- 5.6.3 RAID 10 vs RAID 5 -- 5.6.4 High-performance disk drives -- 5.7 Configuring for performance -- 5.7.1 Host adapters -- 5.7.2 RAID ranks -- 5.7.3 Cache -- 5.7.4 Disk drives -- 5.8 Subsystem Device Driver -- 5.9 Measurement tools -- 5.10 IBM TotalStorage Expert -- 5.10.1 ESS Expert overview -- 5.10.2 How does the ESS Expert work -- 5.10.3 ESS Expert performance reports -- 5.11 z/OS environment tools -- Chapter 6. zSeries performance -- 6.1 Overview -- 6.2 Parallel Access Volume -- 6.2.1 Traditional z/OS behavior -- 6.2.2 Parallel I/O capability -- 6.2.3 Benefits of Parallel Access Volume -- 6.2.4 PAV base and alias addresses -- 6.2.5 PAV tuning -- 6.2.6 Configuring PAVs -- 6.2.7 Querying PAVs -- 6.2.8 PAV assignment -- 6.2.9 WLM support for dynamic PAVs -- 6.2.10 Reassignment of a PAV alias.…”
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Big data : concepts, technology and architecture by Balusamy, Balamurugan, R, Nandhini Abirami, Kadry, Seifedine, 1977-, Gandomi, Amir Hossein

Table of Contents: “…143</p> <p>5.2.3HDFS Architecture. 143</p> <p>5.2.4HDFS Read/Write Operation. 146</p> <p>5.2.5Rack Awareness. 148</p> <p>5.2.6Features of HDFS. 149</p> <p>5.2.6.1Cost-effective. 149</p> <p>5.2.6.2Distributed storage. 149</p> <p>5.2.6.3Data Replication. 149</p> <p>5.3 Hadoop Computation. 149</p> <p>5.3.1MapReduce. 149</p> <p>5.3.1.1Mapper. 151</p> <p>5.3.1.2Combiner. 151</p> <p>5.3.1.3 Reducer. 152</p> <p>5.3.1.4 JobTracker and TaskTracker. 153</p> <p>5.3.2 MapReduce Input Formats. 154</p> <p>5.3.3 MapReduce Example. 156</p> <p>5.3.4 MapReduce Processing. 157</p> <p>5.3.5 MapReduce Algorithm.. 160</p> <p>5.3.6 Limitations of MapReduce. 161</p> <p>5.4Hadoop 2.0. 161</p> <p>5.4.1Hadoop 1.0 limitations. 162</p> <p>5.4.2 Features of Hadoop 2.0. 163</p> <p>5.4.3 Yet Another Resource Negotiator (YARN). 164</p> <p>5.4.3 Core components of YARN.. 165</p> <p>5.4.3.1 ResourceManager. 165</p> <p>5.4.3.2 NodeManager. 166</p> <p>5.4.4 YARN Scheduler. 169</p> <p>5.4.4.1 <i>FIFO scheduler</i>. 169</p> <p>5.4.4.2 <i>Capacity Scheduler</i>. 170</p> <p>5.4.4.3 <i>Fair Scheduler</i>. 170</p> <p>5.4.5 Failures in YARN.. 171</p> <p>5.4.5.1ResourceManager failure. 171</p> <p>5.4.5.2 ApplicationMaster failure. 172</p> <p>5.4.5.3 NodeManagerFailure. 172</p> <p>5.4.5.4 Container Failure. 172</p> <p>5.3 HBASE. 173</p> <p>5.4 Apache Cassandra. 176</p> <p>5.5 SQOOP. 177</p> <p>5.6 Flume. 179</p> <p>5.6.1 Flume Architecture. 179</p> <p>5.6.1.1 Event. 180</p> <p>5.6.1.2 Agent. 180</p> <p>5.7 Apache Avro. 181</p> <p>5.8 Apache Pig. 182</p> <p>5.9 Apache Mahout. 183</p> <p>5.10 Apache Oozie. 183</p> <p>5.10.1 Oozie Workflow.. 184</p> <p>5.10.2 Oozie Coordinators. 186</p> <p>5.10.3 Oozie Bundles. 187</p> <p>5.11 Apache Hive. 187</p> <p>5.11 Apache Hive. 187</p> <p>Hive Architecture. 189</p> <p>Hadoop Distributions. 190</p> <p>Chapter 5refresher. 191</p> <p>Conceptual short questions with answers. 194</p> <p>Frequently asked Interview Questions. 199</p> <p>Chapter Objective. 200</p> <p>6.1 Terminologies of Big Data Analytics. 201</p> <p><i>Data Warehouse</i>. 201</p> <p><i>Business Intelligence</i>. 201</p> <p><i>Analytics</i>. 202</p> <p>6.2 Big Data Analytics. 202</p> <p>6.2.1 Descriptive Analytics. 204</p> <p>6.2.2 Diagnostic Analytics. 205</p> <p>6.2.3 Predictive Analytics. 205</p> <p>6.2.4 Prescriptive Analytics. 205</p> <p>6.3 Data Analytics Lifecycle. 207</p> <p>6.3.1 Business case evaluation and Identify the source data. 208</p> <p>6.3.2 Data preparation. 209</p> <p>6.3.3 Data Extraction and Transformation. 210</p> <p>6.3.4 Data Analysis and visualization. 211</p> <p>6.3.5 Analytics application. 212</p> <p>6.4 Big Data Analytics Techniques. 212</p> <p>6.4.1 Quantitative Analysis. 212</p> <p>6.4.3 Statistical analysis. 214</p> <p>6.4.3.1 A/B testing. 214</p> <p>6.4.3.2 Correlation. 215</p> <p>6.4.3.3 Regression. 218</p> <p>6.5 Semantic Analysis. 220</p> <p>6.5.1 Natural Language Processing. 220</p> <p>6.5.2 Text Analytics. 221</p> <p>6.7 Big Data Business Intelligence. 222</p> <p>6.7.1 Online Transaction Processing (OLTP). 223</p> <p>6.7.2 Online Analytical Processing (OLAP). 223</p> <p>6.7.3 Real-Time Analytics Platform (RTAP). 224</p> <p>6.6Big Data Real Time Analytics Processing. 225</p> <p>6.7 Enterprise Data Warehouse. 227</p> <p>Chapter 6 Refresher. 228</p> <p>Concept…”
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Industrial automation technologies by Dey, Chanchal, Sen, Sunit Kumar

Table of Contents: “…Digital PID Control Algorithm -- Positional and Velocity Forms -- 3.3.4. …”
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IBM TotalStorage : SAN product, design, and optimization guide

Table of Contents: “…-- 3.7.8 FC-PH-2 and speed -- 3.7.9 1, 2 and 4 Gbps and beyond -- 3.7.10 FC-PH, FC-PH-2, and FC-PH-3 -- 3.7.11 Layers -- 3.8 Zoning -- 3.8.1 Hardware zoning -- 3.8.2 Software zoning -- 3.9 Trunking -- 3.9.1 Frame filtering -- 3.9.2 Oversubscription -- 3.9.3 Congestion -- 3.9.4 Information units -- 3.9.5 The movement of data -- 3.9.6 Data encoding -- 3.10 Ordered set, frames, sequences, and exchanges -- 3.10.1 Ordered set -- 3.10.2 Frames -- 3.10.3 Sequences -- 3.10.4 Exchanges -- 3.10.5 Frames -- 3.10.6 In order and out of order -- 3.10.7 Latency -- 3.10.8 Heterogeneousness -- 3.10.9 Open Fiber Control -- 3.11 Fibre Channel Arbitrated Loop (FC-AL) -- 3.11.1 Loop protocols -- 3.11.2 Fairness algorithm -- 3.11.3 Loop addressing -- 3.11.4 Private devices on NL_Ports -- 3.12 Factors and considerations -- 3.12.1 Limits -- 3.12.2 Security -- 3.12.3 Interoperability -- 3.13 Standards -- 3.14 SAN industry associations and organizations -- 3.14.1 Storage Networking Industry Association -- 3.14.2 Fibre Channel Industry Association -- 3.14.3 SCSI Trade Association -- 3.14.4 International Committee for Information Technology Standards -- 3.14.5 INCITS technical committee T11.…”
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AC electric motors control : advanced design techniques and applications

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Introduction to type-2 fuzzy logic control : theory and applications by Mendel, Jerry M., 1938-

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Digital image interpolation in Matlab by Kok, Chi-Wah, Tam, Wing-Shan

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Understanding smart sensors by Frank, Randy

Table of Contents: “…Field Programmable Gate Arrays -- 5.4.3. Algorithms Versus Look-Up Tables -- 5.5. Techniques and Systems Considerations -- 5.5.1. …”
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Statistics for business by Mariappan, Perumal

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Machine Learning for Risk Calculations : A Practitioner's View. by Ruiz, Ignacio

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