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Distinct neural signatures of hippocampal population dynamics during locomotion-in-place. [PDF]

Sci Rep
Inayat S, McAllister BB, Whishaw IQ, Mohajerani MH.   +3 more
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A framework for parameter optimization in mutual information (MI)-based registration algorithms

SPIE Proceedings, 2006
In this paper, we present a framework that one could use to set optimized parameter values, while performing image registration using mutual information as a metric to be maximized. Our experiment details these steps for the registration of X-ray Computer Tomography (CT) images with Positron Emission Tomography (PET) images.
Girish Gopalakrishnan, S. V. Bharath Kumar, Rakesh Mullick, Ajay Narayanan, Srikanth Suryanarayanan   +4 more
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MI-HGRU: A Combine Method of Mutual Information and HGRU Neural Network for Boiler NOx Emission Prediction

2021
Accurately predicting NOx emissions during boiler combustion is of significance for the operation and control of the boiler combustion systems in coal-fired power plants. According to the characteristics of the boiler combustion process with strong disturbances, highly nonlinear and multivariate coupling, a fusion model based on mutual information ...
Kangwei Lin, Hong Xiao, Wenchao Jiang, Jianren Yang, Cong Zhao, Jiarong Lu   +5 more
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Quantitative analysis of coal quality by mutual information-particle swarm optimization (MI-PSO) hybrid variable selection method coupled with spectral fusion strategy of laser-induced breakdown spectroscopy (LIBS) and fourier transform infrared spectroscopy (FTIR)

Spectrochimica Acta Part B: Atomic Spectroscopy, 2021
Abstract Coal quality analysis can provide basic work for the design and operation of related equipment and technological processes, which mainly including ash content and volatile matter. Variable selection plays an important role in the model and properly variable selection methods which can promote the predictive performance of the model and ...
Ting He, Jing Liang, Hongsheng Tang, Tianlong Zhang, Chunhua Yan, Hua Li   +5 more
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TSC-MI: A Temporal Spatial Convolution Neural Network Fused with Mutual Information for Motor Imagery Based EEG Classification

2021
Electroencephalography (EEG) classification is an important part in brain-computer interface system. Motor imagery is a novel experimental paradigm that has been proved effective clinically in recognizing EEG from different limb motions. Our object is to finish motor imagery based EEG classification.
Yonghao Ren, Shuo Zhang 0014, Jing Wang 0080, Runzhi Li   +3 more
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MI-MCF: A Mutual Information-Based Multilabel Causal Feature Selection

IEEE Transactions on Neural Networks and Learning Systems
Multilabel causal feature selection has attracted extensive attention in recent years. Current multilabel causal feature selection algorithms typically employ existing Markov Blanket (MB) search methods for the initial construction of the MB, followed by further optimization.
Lin Ma, Liang Hu 0001, Yonghao Li, Weiping Ding 0001, Wanfu Gao   +4 more
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Multi-modal Image Registration by Quantitative-Qualitative Measure of Mutual Information (Q-MI)

2005
This paper presents a novel measure of image similarity, called quantitative-qualitative measure of mutual information (Q-MI), for multi-modal image registration. Conventional information measure, i.e., Shannon’s entropy, is a quantitative measure of information, since it only considers probabilities, not utilities of events.
Hongxia Luan, Feihu Qi, Dinggang Shen
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Intensity-Modulated Radiation Therapy — Quality Assurance with the Mutual Information Index (MI)

2007
Radiation therapy is an important method of treating neoplastic diseases with ionizing radiation. For this treatment electromagnetic or corpuscular (electrons, protons, neutrons) radiation is used which causes ionization and excitation in the energy absorbing tissue [1].
Astrid Brendemühl, Stefan Ostrowitzki, Uwe Altenburger, J. Christoph Haller, Jürgen Ruhlmann, Thorsten M. Buzug   +5 more
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