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Titlebook: Probability Theory with Applications; M. M. Rao,R. J. Swift Textbook 2006Latest edition Springer-Verlag US 2006 Characteristic functions.C

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ect geometrical equations. The training process of ANN is carried out by incorporating input–output datasets and compiling the MATLAB script file with tuned hyperparameters. From the numerical results, we found that the ANN technique can effectively compute the desired joint angles, a critical facto
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ional layer-based sparse decomposition (CLSD) approach is proposed to recover the original image by half quadratic splitting approach. Due to HQS, the proposed decryption approach is converted to two repetitive steps. The simulation results and the security analyses demonstrate that the proposed ima
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ons systems by masking techniques, financial behavior, networks analysis, nonlinear lasers, numerical modeling, electronic design, and other interesting topics in the area of complex systems. Additionally, there are results on numerical simulation and electronic designs to generate complex dynamic b
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classification of both the chaotic system and its state. This approach extends to multiclass classification, where we employ an error-correcting output codes approach to decompose complex tasks into simpler, binary problems, thereby enhancing both scalability and versatility, as indicated by the re
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Weak Limit Laws The material in this chapter represents a central aspect of analytical probability theory, some of which will be essential for Part III of this book dealing with some important applications. In fact, much of additive process analysis in Chapter 8 depends upon the work of this chapter.
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ch as an urban area). The study of energy metabolism of an economy is insightful on both a local scale (city, region, or country) and on a global scale (world economy). A key feature contributing to the complexity of socioecologic systems is feedback, manifest in the presence of .. Material cycles i
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