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» Neural Model Identification Using Local Robustness Analysis
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128
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MICCAI
2005
Springer
16 years 3 months ago
Physiological System Identification with the Kalman Filter in Diffuse Optical Tomography
Abstract. Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxyand deoxyhemoglobin. When applied to functiona...
Solomon Gilbert Diamond, Theodore J. Huppert, Vill...
IDA
2009
Springer
15 years 9 months ago
Cumulative State Coherence Transform for a Robust Two-Channel Multiple Source Localization
This work presents a novel robust method for a two-channel multiple Time Difference of Arrival (TDOA) estimation. The method is based on a recursive frequency-domain Independent C...
Francesco Nesta, Piergiorgio Svaizer, Maurizio Omo...
125
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BMCBI
2006
124views more  BMCBI 2006»
15 years 2 months ago
Predicting transcription factor binding sites using local over-representation and comparative genomics
Background: Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented tran...
Matthieu Defrance, Hélène Touzet
ICANN
2003
Springer
15 years 7 months ago
Unsupervised Learning of a Kinematic Arm Model
Abstract. An abstract recurrent neural network trained by an unsupervised method is applied to the kinematic control of a robot arm. The network is a novel extension of the Neural ...
Heiko Hoffmann, Ralf Möller
116
Voted
BMCBI
2006
216views more  BMCBI 2006»
15 years 2 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...