Titlebook: Quantitative Neuroscience; Models, Algorithms, P. M. Pardalos,J. C. Sackellares,L. D. Iasemidis Book 2004 Springer Science+Business Media

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書目名稱Quantitative Neuroscience影響因子(影響力)




書目名稱Quantitative Neuroscience影響因子(影響力)學(xué)科排名




書目名稱Quantitative Neuroscience網(wǎng)絡(luò)公開度




書目名稱Quantitative Neuroscience網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Quantitative Neuroscience被引頻次




書目名稱Quantitative Neuroscience被引頻次學(xué)科排名




書目名稱Quantitative Neuroscience年度引用




書目名稱Quantitative Neuroscience年度引用學(xué)科排名




書目名稱Quantitative Neuroscience讀者反饋




書目名稱Quantitative Neuroscience讀者反饋學(xué)科排名

Middle-Ear

Epileptic Seizure Detection Using Dynamical Preprocessing (STLmax),rofiles also show short-term patterns characterizing seizures that can be used for detection purposes. In this paper, we explore two such properties shown by the STL. data during seizures and develop and compare automatic seizure detection algorithms on over 1,000 hours of data.

自愛

Mutter

SNEER

Biocomputinghttp://image.papertrans.cn/q/image/780939.jpg

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https://doi.org/10.1007/978-1-4613-0225-4algorithms; complex system; data mining; diagnostics; dynamical systems; magnetic resonance; magnetic reso

暫時別動

1571-4861 trumenta- tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This verita- ble revolution already has resulted in widespread availability of high resolution neuroimaging devices in clinical as well as resear

Muscularis

不合

FILTH

Optimization Techniques for Independent Component Analysis with Applications to EEG Data,cond and fourth order statistics by joint diagonalization of covariance and cumulant matrices depending on time delays. We describe an experiment with EEG data showing that the combination of second and fourth order statistics gives better results for detecting of eye movements.