NAUT
发表于 2025-3-28 16:57:36
P. A. Pattanaik.]. The statistical analysis of our simulated data shows long-term dependence in the auto-correlations of squared and absolute returns and hyperbolic decay in the tail of the distribution of the raw returns, both with estimated decay parameters in the same range like empirical data. Theoretical anal
Aromatic
发表于 2025-3-28 19:51:35
Ritesh Jha,Vandana Bhattacharjee,Abhijit Mustafi.]. The statistical analysis of our simulated data shows long-term dependence in the auto-correlations of squared and absolute returns and hyperbolic decay in the tail of the distribution of the raw returns, both with estimated decay parameters in the same range like empirical data. Theoretical anal
贝雷帽
发表于 2025-3-29 01:50:37
Arkajyoti Mukherjee,Ritik Srivastava,Vansh Bhatia,Utkarsh,Suneeta Mohanty.]. The statistical analysis of our simulated data shows long-term dependence in the auto-correlations of squared and absolute returns and hyperbolic decay in the tail of the distribution of the raw returns, both with estimated decay parameters in the same range like empirical data. Theoretical anal
Irascible
发表于 2025-3-29 04:55:55
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aptitude
发表于 2025-3-29 10:32:29
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蛤肉
发表于 2025-3-29 11:36:47
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mettlesome
发表于 2025-3-29 17:38:52
,Effective Fusion Technique Using FCM Based Segmentation Approach to Analyze Alzheimer’s Disease,me which is capable to extract important features of each color plane of PET with MRI. The experimental results show that the fused images are the successful combination of anatomical and functional information.
arthroscopy
发表于 2025-3-29 20:31:57
Feature Selection: Role in Designing Smart Healthcare Models,ential attributes, then filtering out the noise (irrelevant attributes) from it and minimize its size without affecting its quality, i.e. after filtrating the attributes, there should not be any required attribute missing which will affect the performance of the predictive models. This task of ident
食草
发表于 2025-3-30 03:14:00
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值得
发表于 2025-3-30 06:42:59
Study of Different Filter Bank Approaches in Motor-Imagery EEG Signal Classification,aining. The obtained classification accuracies are then compared with one another to examine the performance of the proposed approach. The best classification accuracy obtained from our study is 86.43%.