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52. CHAPTER 3: Three-Dimensional Packaging in Multilayer Organic Substrates: 3.4: THREE-DIMENSIONAL PAPER-BASED MODULES FOR RFID/SENSING APPLICATIONS.
53. CHAPTER 11: Final Products: 11.1 TERM PAPERS, THESES, REPORTS, AND PUBLICATIONS.
54. CHAPTER 10: Analysis with an Analytical Model: 10.2 DISCUSSION OF PAPERS.
55. CHAPTER 6: Bottlenecks and Flow Equivalence: 6.4 DISCUSSION OF PAPERS.
56. CHAPTER 8: TRANSMISSION-LINE PARAMETERS: 8.9 DETERMINATION OF IMPEDANCE OF COMPLEX GEOMETRIES USING CONDUCTING -PAPER TECHNIQUES.
57. Chapter 6: Paper and State.
58. CHAPTER 16: Predictions and Observations of SEU Rates in Space: 16.5 CONSTITUENTS OF A GOOD RATE COMPARISON PAPER.
59. Preface.
60. CHAPTER 6: Content: Markup and Genres: 6.3 PAPER GENRES REBORN.
61. CHAPTER 1: Concepts and Little's Law: 1.4 DISCUSSION OF PAPERS.
62. CHAPTER 9: Experimental Validation and Analysis: 9.3 DISCUSSION OF PAPERS.
63. CHAPTER 7: Deterministic Approximations: 7.3 DISCUSSION OF PAPERS.
64. Chapter 6: Paper as Passion: Niklas Luhmann and His Card Index.
65. CHAPTER 6: Misconceptions and Tips for Paper Writing: 6.5 CREATE A HIERARCHY OF SUBSECTIONS AND CHOOSE SECTION TITLES CAREFULLY.
66. Chapter 12: Software Process: Software Processes Are Software Too, Revisited: An Invited Talk on the Most Influential Paper of ICSE 9.
67. Appendix B: File Template for a Double-Column Paper.
68. II APPLICATIONS: 7 Agent-Oriented Methodologies: 7.6 ROADMAP and RAP/AOR.
69. CHAPTER 7: Beyond the Book: 7.1 BEYOND PAPER CAPABILITIES.
70. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.16: Tighter Alternatives to the Cramér-Rao Lower Bound for Discrete-Time Filtering.
71. Part VII Applications: Nonlinear Dynamic Systems: Paper 7.2: A Performance Bound for Manoeuvring Target Tracking Using Best-Fitting Gaussian Distributions.
72. Part II Global Bayesian Bounds: Paper 2.3: Single-Tone Parameter Estimation from Discrete-Time Observations.
73. Part V Applications: Static Parameters: Paper 5.7: OPTIMIZATION OF ELEMENT POSITIONS FOR DIRECTION FINDING WITH SPARSE ARRAYS.
74. Part V Applications: Static Parameters: Paper 5.12: Barankin Bound for Range and Doppler Estimation Using Orthogonal Signal Transmission.
75. Part IV Constrained Cramér--Rao Bounds: Paper 4.8: Properties of Quadratic Covariance Bounds.
76. Part II Global Bayesian Bounds: Paper 2.21: Threshold Region Performance of Maximum Likelihood Direction of Arrival Estimators.
77. Part II Global Bayesian Bounds: Paper 2.10: THE BAYESIAN ABEL BOUND ON THE MEAN SQUARE ERROR.
78. Part II Global Bayesian Bounds: Paper 2.11: Some Lower Bounds on Signal Parameter Estimation.
79. Contents.
80. CHAPTER 6: Misconceptions and Tips for Paper Writing: 6.7 OTHER MISCONCEPTIONS AND FLAWS.
81. CHAPTER 3: Getting Started: Finding New Ideas and Organizing Your Plans: 3.8 LEARNING TO ORGANIZE PAPERS AND IDEAS WELL.
82. CHAPTER 4: Markov Chains: 4.4 DISCUSSION OF PAPERS.
83. CHAPTER 2: Single Queues: 2.4 DISCUSSION OF PAPERS.
84. Appendix A: File Template for a Short Single-Column Report or Paper.
85. Evaluating Ideas.
86. Chapter 1: Historical and Review Papers: Recent Progress of Quasi-Optical Integrated Microwave and Millimeter-Wave Circuits and Components.
87. Part I Bayesian Cramér--Rao Bounds: Paper 1.1: Excerpts from Part I of Detection, Estimation, and Modulation Theory.
88. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.8: Error Bounds for the Nonlinear Filtering of Signals with Small Diffusion Coefficients.
89. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.11: Excerpts from Part II of Detection, Estimation, and Modulation Theory.
90. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.13: Posterior Cramér-Rao Bounds for Discrete-Time Nonlinear Filtering.
91. Part VII Applications: Nonlinear Dynamic Systems: Paper 7.13: Weiss--Weinstein Lower Bounds for Markovian Systems. Part 2: Applications to Fault-Tolerant Filtering.
92. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.14 Filtering, predictive, and smoothing Cramér--Rao bounds for discrete-time nonlinear dynamic systems.
93. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.15: Recursive Weiss-Weinstein Lower Bounds for Discrete-Time Nonlinear Filtering.
94. Part VI Nonlinear Stochastic Dynamic Systems: Paper 6.17: A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking.
95. Part V Applications: Static Parameters: Paper 5.5: Barankin Bounds for Source Localization in an Uncertain Ocean Environment.
96. Part V Applications: Static Parameters: Paper 5.6: A Bayesian Approach to Array Geometry Design.
97. Part VII Applications: Nonlinear Dynamic Systems: Paper 7.12: BAYESIAN CRAMÉR-RAO BOUNDS FOR MULTISTATIC RADAR.
98. Part V Applications: Static Parameters: Paper 5.8: Direction-Or-Arrival Estimation Using Separated Subarrays.
99. Part V Applications: Static Parameters: Paper 5.10: On Geolocation Accuracy with Prior Information in Non-line-of-sight Environment.
100. Part V Applications: Static Parameters: Paper 5.11: On the Application of the Cramer-Rao and Detection Theory Bounds to Mean Square Error of Symbol Timing Recovery.
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