Search Results - empirical algorithm

Statistical analysis techniques in particle physics : fits, density estimation and supervised learning by Narsky, Ilya, Porter, Frank Clifford

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Wireless technologies in intelligent transportation systems

Table of Contents: “…Adaptive Beamforming Algorithms; 4.e.1. Sample Matrix Inversion (SMI) Algorithm; 4.e.2. …”
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Wireless communications systems design by Kim, Haesik

Table of Contents: “…6.1.2 Example of Turbo Encoding and Decoding6.1.3 Hardware Implementation of Turbo Encoding and Decoding; 6.2 Turbo Product Codes; 6.2.1 Turbo Product Encoding and Decoding Algorithm; 6.2.2 Example of Turbo Product Encoding and Decoding; 6.2.3 Hardware Implementation of Turbo Product Encoding and Decoding; 6.3 Low-Density Parity Check Codes; 6.3.1 LDPC Encoding and Decoding Algorithms; 6.3.2 Example of LDPC Encoding and Decoding; 6.3.3 Hardware Implementation of LDPC Encoding and Decoding; 6.4 Problems; References; Chapter 7 Orthogonal Frequency-Division Multiplexing; 7.1 OFDM System Design.…”
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Discourse, of course : an overview of research in discourse studies

Table of Contents: “…Bateman -- Schemes and tropes in visual communication : the case of object grouping in advertisements / Alfons Maes and Joost Schilperoord -- Text types and dynamism of genres / Sungsoon Wang -- Academic and professional written genres in disciplinary communication : theoretical and empirical challenges / Giovanni Parodi -- Why investigate textual information hierarchy? …”
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Retail futures : the good, the bad and the ugly of the digital transformation

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Marvels of Artificial and Computational Intelligence in Life Sciences. by Sivaraman, Thirunavukkarasu

Table of Contents: “…Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Foreword I -- Foreword II -- Preface -- List of Contributors -- Artificial Intelligence for Infectious Disease Surveillance -- Sathish Sankar1,*, Pitchaipillai Sankar Ganesh1 and Rajalakshmanan Eswaramoorthy2 -- INTRODUCTION -- CONCLUSION -- ACKNOWLEDGEMENT -- REFERENCES -- Recent Innovations in Artificial Intelligence (AI) Algorithms in Electrical and Electronic Engineering for Future Transformations…”
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The importance of health informatics in public health during a pandemic

Table of Contents: “…Confirmatory Factors to Nursing Practice for Patient Safety of Nurses in Kalasin Hospital, Kalasin Province, Thailand -- Patient Awareness of the Severity of Their Information and Medication Management-Related Adverse Events -- The Quality Improvement Information System for Surveillance and Monitoring for Patient Safety and Personal Safety in Kalasin Hospital, Kalasin Province, Thailand -- Iconic Visualization of Sickle Cell Patients Current and Past Health Status -- Using Machine Learning Algorithms to Predict Antimicrobial Resistance and Assist Empirical Treatment…”
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Applied Artificial Intelligence : Proceedings of the 7th International FLINS Conference. by Arena, Paolo, Fortuna, Luigi

Table of Contents: “…Environmental/economic dispatch using genetic algorithm and fuzzy number ranking method / G. Zhang [and others]. …”
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Oil and gas exploration : methods and application

Table of Contents: “…Theory; 3.2.1. EMD Algorithm; 3.2.2. Gaussian Noise Model and EMD Signal Denoising; 3.2.3. …”
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Other geographies : the influences of Michael Watts

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Social-behavioral modeling for complex systems

Table of Contents: “…Cover; Title Page; Copyright; Contents; Foreword; List of Contributors; About the Editors; About the Companion Website; Part I Introduction and Agenda; Chapter 1 Understanding and Improving the Human Condition: A Vision of the Future for Social-Behavioral Modeling; Challenges; Challenge One: The Complexity of Human Issues; Challenge Two: Fragmentation; Empirical Observation; Empirical Experiments; Generative Simulation; Unification; Challenge Three: Representations; Challenge Four: Applications of Social-Behavioral Modeling; About This Book; Roadmap for the Book; References…”
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Combinatorial Development Of Solid Catalytic Materials : Design Of High-Throughput Experiments, Data Analysis, Data Mining.

Table of Contents: “…Tuning Evolutionary Algorithms with Artificial Neural Networks (M. Holena) -- 7.1. …”
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EEG Signal Processing and Machine Learning. by Sanei, Saeid

Table of Contents: “…3.6 Dynamic Modelling of Neuron Action Potential Threshold -- 3.7 Summary -- References -- Chapter 4 Fundamentals of EEG Signal Processing -- 4.1 Introduction -- 4.2 Nonlinearity of the Medium -- 4.3 Nonstationarity -- 4.4 Signal Segmentation -- 4.5 Signal Transforms and Joint Time-Frequency Analysis -- 4.5.1 Wavelet Transform -- 4.5.1.1 Continuous Wavelet Transform -- 4.5.1.2 Examples of Continuous Wavelets -- 4.5.1.3 Discrete-Time Wavelet Transform -- 4.5.1.4 Multiresolution Analysis -- 4.5.1.5 Wavelet Transform Using Fourier Transform -- 4.5.1.6 Reconstruction -- 4.5.2 Synchro-Squeezed Wavelet Transform -- 4.5.3 Ambiguity Function and the Wigner-Ville Distribution -- 4.6 Empirical Mode Decomposition -- 4.7 Coherency, Multivariate Autoregressive Modelling, and Directed Transfer Function -- 4.8 Filtering and Denoising -- 4.9 Principal Component Analysis -- 4.9.1 Singular Value Decomposition -- 4.10 Summary -- References -- Chapter 5 EEG Signal Decomposition -- 5.1 Introduction -- 5.2 Singular Spectrum Analysis -- 5.2.1 Decomposition -- 5.2.2 Reconstruction -- 5.3 Multichannel EEG Decomposition -- 5.3.1 Independent Component Analysis -- 5.3.2 Instantaneous BSS -- 5.3.3 Convolutive BSS -- 5.3.3.1 General Applications -- 5.3.3.2 Application of Convolutive BSS to EEG -- 5.4 Sparse Component Analysis -- 5.4.1 Standard Algorithms for Sparse Source Recovery -- 5.4.1.1 Greedy-Based Solution -- 5.4.1.2 Relaxation-Based Solution -- 5.4.2 k-Sparse Mixtures -- 5.5 Nonlinear BSS -- 5.6 Constrained BSS -- 5.7 Application of Constrained BSS -- Example -- 5.8 Multiway EEG Decompositions -- 5.8.1 Tensor Factorization for BSS -- 5.8.2 Solving BSS of Nonstationary Sources Using Tensor Factorization -- 5.9 Tensor Factorization for Underdetermined Source Separation -- 5.10 Tensor Factorization for Separation of Convolutive Mixtures in the Time Domain.…”
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Progress in financial markets research

Table of Contents: “…Optimization of Technical Rules by Genetic Algorithms -- 8.5. Empirical Results -- Conclusion -- References -- Chapter 9: MODERN ANALYSIS OF FLUCTUATIONSIN FINANCIAL TIME SERIES AND BEYOND -- 9.1. …”
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Enhance Oil and Gas Exploration with Data-Driven Geophysical and Petrophysical Models. by Holdaway, Keith R.

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Inverse problems of vibrational spectroscopy by Yagola, A. G.

Table of Contents: “…Semiempirical methods -- 3.5. Empirical methods -- Chapter 4. Vibrational problem in internal coordinates. …”
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Data mining with decision trees : theory and applications by Rokach, Lior

Table of Contents: “…2.1 Algorithmic Framework for Decision Trees2.2 Stopping Criteria; 3. …”
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A Case for the Existence of God. by Overman, Dean L.

Table of Contents: “…Chapter 11: Recorded Experiences of Encounters with the Divine Bear Witness to a Way of Knowing that Includes Kierkegaard's KENDSKAB, BUBER'S I-Thou, OTTO'S Wholly Other, AND MARCEL'S MysteryChapter 12: THESE NINE WITNESSES TESTIFY TO ANOTHER WAY OF KNOWING THAT IS COMPATIBLE WITH THE EMPIRICAL AND THE METAPHYSICAL RATIONAL WAYS OF KNOWING, BUT IS BEYOND THE DESCRIBABLE AND REQUIRES PERSO; Chapter 13: CONCLUDING REFLECTIONS AND SUMMARY; AFTERWORD; Appendix A: THE NEW MATHEMATICS OF ALGORITHMIC INFORMATION THEORY IS RELEVANT TO THEORIES CONCERNING THE FORMATION OF THE FIRST LIVING MATTER.…”
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Applications of GRA and grey prediction models

Table of Contents: “…Combined forecasting of regional logistics demand optimized by genetic algorithmApplication of grey relational analysis to expose individual student's cognitive difficulties in English public speaking; Mobile communication service income prediction method based on grey buffer operator theory; Using grey relational analysis to evaluate resource configuration and service ability for hospital on public private partnership model in China; The status of traditional medicine and national medicine in different areas of the China in 2011 with grey clustering analysis.…”
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Computational materials discovery

Table of Contents: “…3.1.2 Empirical Interatomic Potentials3.1.3 Machine Learning Interatomic Potentials; 3.2 Simple Problem: Fitting of Potential Energy Surfaces; 3.2.1 Representation of Atomic Systems; 3.2.2 An Overview of Machine Learning Methods; 3.3 Machine Learning Interatomic Potentials; 3.3.1 Representation of Atomic Environments; 3.3.2 Existing MLIPs; 3.4 Fitting and Testing of Interatomic Potentials; 3.4.1 Optimization Algorithms; 3.4.2 Validation and Cross-validation; 3.4.3 Learning on the Fly; 3.5 Discussion; 3.5.1 Which Potential Is Better?…”
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