Laplace & Fourier Transforms: A simple explanation

di Theodoros Kostis (Autore)

Theodoros Kostis, 2024

Contents Introduction1 Essence of Fourier Transform2 Simple Explanation with a metaphor2 Essence4 Key aspects of the Fourier Transform5 Laplace Transform9 Laplace Transforms10 Essence of Laplace Transform10 Laplace & Periodic Functions11 Special Points12 Signal processing and communication systems13 "s" Variable14 MATLAB Example16 Fourier Transform17 Time Domain & Frequency Domain18 Time Domain18 Frequency Domain19 MATLAB Example20 Laplace & Fourier Transform Connection24 Laplace & Fourier Transforms25 Connection25 Connection between Laplace & Fourier Transforms26 Mathematical Formulation:26 More Comparisons27 Quantum Fourier Transform29 Quantum Fourier Transform30 A Gateway to Quantum Computing30 What is the Quantum Fourier Transform?30 Essence of the Quantum Fourier Transform30 Applications of the Quantum Fourier Transform31 Conclusion: Pioneering the Quantum Frontier31 Is there an application where QFT is used? Artificial Intelligence in EW33 Artificial Intelligence in Electronic Warfare34 AI algorithms with best application to electronic warfare34 Machine Learning (ML)34 Reinforcement Learning (RL)34 Deep Learning (DL) 34 Genetic Algorithms (GA) 34 Swarm Intelligence34 Expert Systems34 Game Theory35 Conclusions35 Fourier Transforms in AI36 Signal Processing36 Image Processing36 Natural Language Processing (NLP)36 Machine Learning Feature Extraction36 Conclusions37 Fourier Transforms for Electronic Protection38 Signal Analysis and Processing38 Detection and Identification of Threats38 Electronic Counter-Countermeasures (ECCM)38 Radar and Communication System Enhancements39 Stealth and Anti-Stealth Technologies39 Software-Defined Radio (SDR) and Cognitive EW39 Conclusions40 Signal Processing in Electronic Warfare Receivers41 Signal Reception41 Preprocessing41 Downconversion41 Analog-to-Digital Conversion (ADC)41 Digital Signal Processing (DSP)42 Postprocessing42 Additional Considerations42 Summary43 Machine Learning Techniques for Signal Classification Post-Fourier Transform44 Supervised Learning44 1.1. Support Vector Machines (SVM)44 1.2. Neural Networks44 1.3. k-Nearest Neighbors (k-NN)44 1.4. Decision Trees and Random Forests44 Unsupervised Learning45 2.1. Clustering45 2.2. Principal Component Analysis (PCA)45 Semi-Supervised and Reinforcement Learning45 3.1. Semi-Supervised Learning45 3.2. Reinforcement Learning46 Implementation Considerations46 Conclusions46 Laplace Transform & Analog Filters48 Analog Filters49 Electronic Warfare49 System Modeling49 Specification Analysis49 Filter Design50 Analysis and Optimization 50 Implementation and Validation50 Conclusions50 Fourier Transform for Filters51 Fourier Transform for Analog Filters52 Analog Filters52 Signal Representation52 Frequency Response Specification52 Filter Design52 Frequency Domain Analysis53 Optimization and Refinement53 Implementation and Validation53 Conclusions53 Discrete Fourier Transform for Digital Filters55 Digital Filters55 Analog Filters55 Laplace Transform55 Digital Filters55 Z-Transform56 Conclusions56

• Autore: Theodoros Kostis
• Anno edizione: 2024
• Editore: Theodoros Kostis
• Formato: EPUB2 con DRMFREE
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9798227079855

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