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A Review on Machine Learning for EEG Signal Processing in Bioengineering
IEEE Reviews in Biomedical Engineering, 2020Electroencephalography (EEG) has been a staple method for identifying certain health conditions in patients since its discovery. Due to the many different types of classifiers available to use, the analysis methods are also equally numerous.
M. Hosseini, Amin Hosseini, Kiarash Ahi
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Signal Processing and Signal Processing Models
1993In this chapter we will examine some of the characteristics of the dolphin sonar signal from a signal processing point of view. Several sections will also be devoted to the discussion of signal processing techniques and the construction of mathematical models and electronic analogs to the dolphin sonar signal processing system. These models and analogs
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Proximal Splitting Methods in Signal Processing
Fixed-Point Algorithms for Inverse Problems in Science and Engineering, 2009The proximity operator of a convex function is a natural extension of the notion of a projection operator onto a convex set. This tool, which plays a central role in the analysis and the numerical solution of convex optimization problems, has recently ...
P. Combettes, J. Pesquet
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2015
This chapter covers signals and signal processing. It presents a unified treatment of signals and interrupts, which helps put signals into a proper perspective. It treats signals as interrupts to processes, which diverts a process from its normal executions to do signal processing.
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This chapter covers signals and signal processing. It presents a unified treatment of signals and interrupts, which helps put signals into a proper perspective. It treats signals as interrupts to processes, which diverts a process from its normal executions to do signal processing.
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1971
It is very important that methods be developed to extract signals from the noisy backgrounds that usually accompany them. Signal processing has, therefore, become an important field in communications and in acoustics. The human ear processes the information it receives and does a reasonably good job of filtering.
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It is very important that methods be developed to extract signals from the noisy backgrounds that usually accompany them. Signal processing has, therefore, become an important field in communications and in acoustics. The human ear processes the information it receives and does a reasonably good job of filtering.
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2016
Digital signal processing algorithms are recursive in nature. These algorithms are explained by iterative data-flow graphs where nodes represent computations and edges represent communications. For all data-flow graphs, time taken to achieve output from the applied input is referred as iteration bound.
David K. Mellinger +3 more
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Digital signal processing algorithms are recursive in nature. These algorithms are explained by iterative data-flow graphs where nodes represent computations and edges represent communications. For all data-flow graphs, time taken to achieve output from the applied input is referred as iteration bound.
David K. Mellinger +3 more
openaire +2 more sources
Introduction to Digital Signal Processing
Digital Signal Processing, 2021Li Tan, Jean Jiang
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Two decades of array signal processing research: the parametric approach
IEEE Signal Processing Magazine, 1996H. Krim, M. Viberg
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