Signal processing techniques applied to human sleep EEG signals—A review

2014 ◽  
Vol 10 ◽  
pp. 21-33 ◽  
Author(s):  
Shayan Motamedi-Fakhr ◽  
Mohamed Moshrefi-Torbati ◽  
Martyn Hill ◽  
Catherine M. Hill ◽  
Paul R. White
Keyword(s):  
Signal Processing ◽  
Sleep Eeg ◽  
Eeg Signals ◽  
Human Sleep ◽  
Processing Techniques ◽  
Signal Processing Techniques

The added value of the electrical neuroimaging for the evaluation of marketing stimuli

2012 ◽  
Vol 60 (3) ◽  
pp. 419-426 ◽  
Author(s):  
G. Vecchiato ◽  
J. Toppi ◽  
L. Astolfi ◽  
F. Cincotti ◽  
F. De Vico Fallani ◽  
...  
Keyword(s):  
Signal Processing ◽  
Cognitive Process ◽  
New Products ◽  
Added Value ◽  
Eeg Signals ◽  
Electrical Neuroimaging ◽  
Processing Techniques ◽  
Signal Processing Techniques ◽  
Area Of Study

Abstract There is a large interest in the marketing world to use the neuroimaging tools as a possible aid to evaluate the efficacy of a commercial advertisement. Such an area of study is called “neuromarketing”. Here we illustrate some applications of electrical neuroimaging, a discipline using EEG and intensive signal processing techniques for the evaluation of such marketing stimuli. We will show which kind of information is possible to gather with these methodologies while persons are watching marketing relevant stimuli. Such information is related to the memorization and attention of commercial advertisements. We noted that temporal and frequency patterns of EEG signals are able to return descriptors of cognitive process in subjects that watched such commercial announcements. The described EEG methodologies could be then employed both to better design new products that are going to be promoted on the market as well as to analyse the global cognitive impact of commercial videos already broadcasted.

Automotive Radars

2017 ◽  
Author(s):  
Sujeet Patole ◽  
Murat Torlak ◽  
Dan Wang ◽  
Murtaza Ali
Keyword(s):  
Signal Processing ◽  
Pedestrian Detection ◽  
Radar Signal ◽  
Automotive Radar ◽  
Estimation Algorithms ◽  
Radar Systems ◽  
Starting Point ◽  
Processing Techniques ◽  
Automotive Radars ◽  
Signal Processing Techniques

Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter- wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade-off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird’s-eye view to the existing research community.

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