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1 | (8) |
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1 | (2) |
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3 | (5) |
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8 | (1) |
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9 | (26) |
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9 | (2) |
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Simulation vs. Optimization |
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11 | (1) |
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Process Models for Imaging and Analysis |
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12 | (4) |
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Fluid Flow and Mixing Models |
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12 | (2) |
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Data- and Image-Driven Models |
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14 | (2) |
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Process Modeling for Design, Control, and Diagnostics |
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16 | (19) |
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16 | (4) |
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20 | (2) |
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22 | (6) |
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28 | (2) |
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30 | (5) |
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Direct Imaging Technology |
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35 | (50) |
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36 | (1) |
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36 | (7) |
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36 | (1) |
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36 | (2) |
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38 | (1) |
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Argon-Ion and Krypton-Ion Lasers |
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39 | (1) |
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40 | (1) |
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40 | (1) |
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41 | (2) |
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43 | (17) |
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43 | (1) |
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43 | (2) |
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45 | (2) |
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Differences between CCD and CMOS Sensors |
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47 | (1) |
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47 | (3) |
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50 | (1) |
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50 | (1) |
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Image Intensifier Designs |
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51 | (1) |
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52 | (1) |
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53 | (2) |
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55 | (1) |
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55 | (1) |
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55 | (1) |
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Detector Elements for Infrared Light |
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56 | (1) |
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57 | (1) |
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Thermochromic Liquid Crystals |
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58 | (1) |
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59 | (1) |
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60 | (8) |
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Glass Materials for Optics |
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60 | (2) |
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62 | (1) |
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62 | (2) |
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64 | (3) |
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67 | (1) |
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68 | (13) |
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Particle Imaging Velocimetry |
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68 | (2) |
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70 | (2) |
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Measurement of pH and Temperature by Fluorescence |
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72 | (1) |
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Dependency on pH and Temperature |
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73 | (1) |
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74 | (1) |
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75 | (2) |
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Micro Shear-Stress Imaging Chip |
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77 | (1) |
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Basic Structure and Calibration |
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77 | (2) |
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79 | (2) |
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81 | (4) |
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83 | (2) |
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85 | (42) |
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85 | (12) |
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Tomography and Tomographic Reconstruction |
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86 | (2) |
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88 | (3) |
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Links with Medical Tomography |
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91 | (1) |
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Historical Developments in Process Tomography |
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92 | (5) |
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Tomographic Sensor Modalities |
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97 | (11) |
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97 | (1) |
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CT and Gamma-Ray Tomography |
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97 | (1) |
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98 | (1) |
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99 | (1) |
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100 | (2) |
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Acoustic and Ultrasonic Methods |
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102 | (3) |
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Other Modalities Borrowed from Medicine |
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105 | (1) |
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Magnetic Resonance Imaging |
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105 | (1) |
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Positron Emission Tomography |
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106 | (1) |
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107 | (1) |
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108 | (7) |
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110 | (2) |
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112 | (1) |
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112 | (2) |
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Model-Based Reconstruction |
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114 | (1) |
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Heuristic and Neural Net Methods |
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114 | (1) |
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Current Tomography Systems |
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115 | (4) |
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115 | (1) |
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116 | (3) |
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119 | (8) |
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119 | (8) |
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Image Processing and Feature Extraction |
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127 | (80) |
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128 | (2) |
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130 | (16) |
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Basic Gray-Level Transformations |
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130 | (1) |
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131 | (1) |
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131 | (1) |
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132 | (1) |
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133 | (4) |
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137 | (1) |
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137 | (4) |
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141 | (3) |
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Frequency Domain Processing |
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144 | (2) |
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146 | (9) |
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146 | (4) |
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150 | (1) |
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150 | (1) |
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151 | (1) |
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151 | (1) |
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Frequency Domain Filtering |
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152 | (1) |
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152 | (1) |
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152 | (2) |
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154 | (1) |
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155 | (13) |
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155 | (1) |
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156 | (1) |
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156 | (2) |
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Parameter Space and Image Space |
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158 | (1) |
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Generalized Hough Transform |
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159 | (2) |
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161 | (1) |
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162 | (1) |
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162 | (3) |
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165 | (1) |
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166 | (2) |
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168 | (14) |
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168 | (2) |
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170 | (4) |
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174 | (2) |
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Shape Features and Representation |
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176 | (1) |
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176 | (2) |
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178 | (2) |
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180 | (2) |
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Morphological Image Processing and Analysis |
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182 | (25) |
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Morphological Transformations of Binary Images |
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182 | (1) |
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Morphological Set Transformations |
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182 | (1) |
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183 | (1) |
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183 | (1) |
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183 | (1) |
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184 | (6) |
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Morphological Transformations of Grayscale Images |
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190 | (2) |
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Hit-or-Miss Transformation |
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192 | (3) |
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195 | (1) |
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196 | (1) |
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Applications of Morphological Processing |
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197 | (1) |
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Image Processing and Analysis |
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198 | (2) |
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200 | (1) |
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Biomedical and Medical Imaging |
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201 | (1) |
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201 | (1) |
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Machine Vision and Inspection |
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201 | (1) |
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201 | (1) |
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202 | (5) |
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207 | (30) |
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207 | (4) |
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State Space Representation of Dynamical Systems |
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208 | (2) |
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Applications to Imaging and Control |
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210 | (1) |
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Real-Time Recursive Estimation: Kalman Predictors and Filters |
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211 | (2) |
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On-Line and Transient Estimation: Smoothers |
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213 | (2) |
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Nonlinear and Non-Gaussian State Estimation |
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215 | (4) |
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215 | (2) |
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Sampling and Particle Filters |
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217 | (2) |
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Partially Unknown Models: Parameter Estimation |
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219 | (2) |
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Batch-Type Optimization: Time-Invariant Parameters |
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220 | (1) |
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Augmented State Models: Time-Varying Parameters |
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220 | (1) |
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221 | (5) |
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General Modeling Issues and Inverse Problems |
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221 | (2) |
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Construction of the Finite Dimensional Discrete-Time Evolution Model |
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223 | (2) |
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Higher Order Evolution Models |
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225 | (1) |
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Stability and Computational Issues |
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225 | (1) |
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Observation and Evolution Models in the Process Industry |
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226 | (1) |
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226 | (1) |
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226 | (1) |
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Example: Convection--Diffusion Models |
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226 | (11) |
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Impedance Tomography and the Measurement Model |
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228 | (1) |
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Convection-Diffusion Model |
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229 | (1) |
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Example 1: Known Velocity Field |
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230 | (2) |
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Example 2: Unknown Rate of Flow |
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232 | (1) |
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232 | (5) |
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237 | (26) |
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237 | (3) |
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240 | (2) |
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242 | (4) |
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246 | (11) |
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Controllability and Observability |
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246 | (3) |
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Linear Quadratic Gaussian Control |
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249 | (3) |
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252 | (5) |
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Practicalities of Implementing Controllers |
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257 | (3) |
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257 | (2) |
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259 | (1) |
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Computer-Based Implementation |
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259 | (1) |
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260 | (3) |
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260 | (3) |
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Imaging Diagnostics for Combustion Control |
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263 | (36) |
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263 | (2) |
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265 | (6) |
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Internal Combustion Engines |
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267 | (3) |
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270 | (1) |
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270 | (1) |
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271 | (6) |
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271 | (1) |
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271 | (2) |
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273 | (3) |
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276 | (1) |
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Results from Combustor Imaging |
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277 | (14) |
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277 | (13) |
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290 | (1) |
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291 | (1) |
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291 | (8) |
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292 | (7) |
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Multiphase Flow Measurements |
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299 | (34) |
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299 | (1) |
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300 | (9) |
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A Priori Knowledge Approach |
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301 | (6) |
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307 | (2) |
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309 | (12) |
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2D Instantaneous and Average Phase Distribution |
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309 | (8) |
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317 | (4) |
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Solids Mass Flow Measurements |
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321 | (12) |
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330 | (3) |
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Applications in the Chemical Process Industry |
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333 | (26) |
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333 | (2) |
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Applications Related to Process Control |
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335 | (15) |
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335 | (3) |
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338 | (2) |
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340 | (3) |
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343 | (1) |
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344 | (2) |
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Compounding of Reinforced Polymers |
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346 | (4) |
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Applications Related to Process and Product R&D |
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350 | (6) |
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Polymerization Monitoring |
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350 | (2) |
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352 | (4) |
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356 | (3) |
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356 | (3) |
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Mineral and Material Processing |
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359 | (42) |
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Motivation for Development of Image-Based Techniques |
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359 | (2) |
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Design of Comminution Equipment |
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361 | (6) |
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External High-Speed Video Imaging of Bead Movement |
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362 | (3) |
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Internal Bead Tracking Using Positron Emission Particle Tracking |
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365 | (2) |
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Granular Flow and Bulk Transportation |
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367 | (9) |
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367 | (7) |
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374 | (2) |
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Particle Classification in Cyclones |
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376 | (9) |
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378 | (5) |
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383 | (2) |
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Performance of Flotation Cells and Columns |
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385 | (5) |
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EIT Analysis of Bubble Columns and Foams |
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385 | (1) |
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Direct Imaging of Flotation Foams |
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386 | (4) |
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Solids Settling and Water Recovery |
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390 | (3) |
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Microscale Analysis of Granules, Flocs, and Sediments |
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393 | (4) |
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397 | (4) |
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397 | (4) |
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Applications in the Metals Production Industry |
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401 | (34) |
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401 | (2) |
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Detection of Slag Entrainment |
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403 | (5) |
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404 | (1) |
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Electromagnetic Detection |
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405 | (2) |
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407 | (1) |
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407 | (1) |
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Measurement of Furnace Refractory Wear |
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408 | (7) |
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408 | (3) |
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411 | (3) |
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414 | (1) |
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415 | (1) |
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415 | (9) |
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Monitoring of Flow Regimes in the Continuous Caster |
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416 | (4) |
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Electromagnetic Monitoring of Flow through Tapholes |
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420 | (1) |
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Imaging of Flow in Ladle Stirring |
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421 | (3) |
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Imaging Solid State Phase Change |
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424 | (5) |
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426 | (1) |
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426 | (3) |
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429 | (6) |
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429 | (6) |
Index |
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435 | |