Search results for "curse of dimensionality"
showing 10 items of 100 documents
1,4-Bis(arylthio)but-2-enes as Assembling Ligands for (Cu2X2)n (X = I, Br; n = 1, 2) Coordination Polymers: Aryl Substitution, Olefin Configuration, …
2016
CuI reacts with E-PhS(CH2CH═CHCH2)SPh, L1, to afford the coordination polymer (CP) [Cu2I2{μ-E-PhS(CH2CH═CHCH2)SPh}2]n (1a). The unprecedented square-grid network of 1 is built upon alternating two-dimensional (2D) layers with an ABAB sequence and contains rhomboid Cu2(μ2-I)2 clusters as secondary building units (SBUs). Notably, layer A, interconnected by bridging L1 ligands, contains exclusively dinuclear units with short Cu···Cu separations [2.6485(7) A; 115 K]. In contrast, layer B exhibits Cu···Cu distances of 2.8133(8) A. The same network is observed when CuBr reacts with L1. In the 2D network of [Cu2Br2{μ-E-PhS(CH2CH═CHCH2)SPh}2]n (1b), isotype to 1a, one square-grid-type layer contain…
Communication between iron(II) building blocks in cooperative spin transition phenomena
2003
[EN] In the present article we discuss the cooperative nature of the spin crossover phenomenon in iron(II) complexes, providing a perspective of the state of the art in this area. The first aspect we discuss is the role of the intermolecular interactions, more precisely the ¿-interactions, in mononuclear complexes. We show that by playing with the nature of the ligands, aliphatic, aromatic, or extended aromatic, it is possible to create stronger cohesive forces and receive a more cooperative response from the compound. In the next step the singular family of bipyrimidine-bridged iron(II) dinuclear compounds is presented as the simplest example of polynuclear spin crossover complexes exhibit…
Ledrappier-Young formula and exact dimensionality of self-affine measures
2017
In this paper, we solve the long standing open problem on exact dimensionality of self-affine measures on the plane. We show that every self-affine measure on the plane is exact dimensional regardless of the choice of the defining iterated function system. In higher dimensions, under certain assumptions, we prove that self-affine and quasi self-affine measures are exact dimensional. In both cases, the measures satisfy the Ledrappier-Young formula. peerReviewed
Measuring Functional Connectivity of Human Intra-Cortex Regions with Total Correlation
2021
The economy of brain organization makes the primate brain consume less energy but efficiency. The neurons densely wired each other dependent on both anatomy structure connectivity and functional connectivity. Here, I only describe functional connectivity with Functional Magnetic Resonance Imaging (fMRI) data. Most importantly, how to quantitative measure information share or separate among functional brain regions, what’s worse, fMRI data exist large dimensional problems or “curse dimensionality” [1]. However, the multivariate total correlation method can perfectly address the above problems. In this paper, two things measured with the information-theoretic technique - total correlation [2,…
Merging Features from Green's Functions and Time Dependent Density Functional Theory: A Route to the Description of Correlated Materials out of Equil…
2016
We propose a description of nonequilibrium systems via a simple protocol that combines exchange-correlation potentials from density functional theory with self-energies of many-body perturbation theory. The approach, aimed to avoid double counting of interactions, is tested against exact results in Hubbard-type systems, with respect to interaction strength, perturbation speed and inhomogeneity, and system dimensionality and size. In many regimes, we find significant improvement over adiabatic time dependent density functional theory or second Born nonequilibrium Green's function approximations. We briefly discuss the reasons for the residual discrepancies, and directions for future work.
Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions
2017
The modular control hypothesis suggests that motor commands are built from precoded modules whose specific combined recruitment can allow the performance of virtually any motor task. Despite considerable experimental support, this hypothesis remains tentative as classical findings of reduced dimensionality in muscle activity may also result from other constraints (biomechanical couplings, data averaging or low dimensionality of motor tasks). Here we assessed the effectiveness of modularity in describing muscle activity in a comprehensive experiment comprising 72 distinct point-to-point whole-body movements during which the activity of 30 muscles was recorded. To identify invariant modules o…
Computing variations of entropy and redundancy under nonlinear mappings not preserving the signal dimension: quantifying the efficiency of V1 cortex
2021
In computational neuroscience, the Efficient Coding Hypothesis argues that the neural organization comes from the optimization of information-theoretic goals [Barlow Proc.Nat.Phys.Lab.59]. A way to confirm this requires the analysis of the statistical performance of biological systems that have not been statistically optimized [Renart et al. Science10, Malo&Laparra Neur.Comp.10, Foster JOSA18, Gomez-Villa&Malo J.Neurophysiol.19]. However, when analyzing the information-theoretic performance, cortical magnification in the retina-cortex pathway poses a theoretical problem. Cortical magnification stands for the increase the signal dimensionality [Cowey&Rolls Exp. Brain Res.74]. Conventional mo…
Gear classification and fault detection using a diffusion map framework
2015
This article proposes a system health monitoring approach that detects abnormal behavior of machines. Diffusion map is used to reduce the dimensionality of training data, which facilitates the classification of newly arriving measurements. The new measurements are handled with Nyström extension. The method is trained and tested with real gear monitoring data from several windmill parks. A machine health index is proposed, showing that data recordings can be classified as working or failing using dimensionality reduction and warning levels in the low dimensional space. The proposed approach can be used with any system that produces high-dimensional measurement data. peerReviewed
An Efficient Network Log Anomaly Detection System Using Random Projection Dimensionality Reduction
2014
Network traffic is increasing all the time and network services are becoming more complex and vulnerable. To protect these networks, intrusion detection systems are used. Signature-based intrusion detection cannot find previously unknown attacks, which is why anomaly detection is needed. However, many new systems are slow and complicated. We propose a log anomaly detection framework which aims to facilitate quick anomaly detection and also provide visualizations of the network traffic structure. The system preprocesses network logs into a numerical data matrix, reduces the dimensionality of this matrix using random projection and uses Mahalanobis distance to find outliers and calculate an a…
Improving statistical classification methods and ecological status assessment for river macroinvertebrates
2016
Aquatic ecosystems are facing a growing number of human-induced stressors and the need to implement more biomonitoring to assess the ecological status of water bodies is eminent. This dissertation aims at providing tools to reduce the costs and improve the accuracy of freshwater benthic macroinvertebrate biomonitoring. To improve the cost-e ciency, we consider automated classi cation and develop a novel classi er suitable for complex macroinvertebrate image data. To enhance the accuracy of macroinvertebrate biomonitoring, we study the statistical properties of the Percent Model A nity index crucial to current Finnish biomonitoring and the factors a ecting these statistics. Finally, we perfo…