检索结果-内蒙古大学图书馆

A model of reward-modulated motor learning with parallel cortical and basal ganglia pathways

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Pyle, Ryan Rosenbaum, Robert Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN United States Interdisciplinary Center for Network Science and Applications University of Notre Dame Notre DameIN United States

Reservoir computing is a biologically inspired class of learning algorithms in which the intrinsic dynamics of a recurrent neural network are mined to produce target time series. Most existing reservoir computing algorithms rely on fully supervised learning rules, which require access to an exact copy of the target response, greatly reducing the utility of the system. Reinforcement learning rules have been developed for reservoir computing, but we find that they fail to converge on complex motor tasks. Current theories of biological motor learning pose that early learning is controlled by dopamine modulated plasticity in the basal ganglia that trains parallel cortical pathways through unsupervised plasticity as a motor task becomes well-learned. We developed a novel learning algorithm for reservoir computing that models the interaction between reinforcement and unsupervised learning observed in experiments. This novel learning algorithm converges on simulated motor tasks on which previous reservoir computing algorithms fail, and reproduces experimental findings that relate Parkinson’s disease and its treatments to motor learning. Hence, incorporating biological theories of motor learning improves the effectiveness and biological relevance of reservoir computing models. Copyright © 2018, The Authors. All rights reserved.

关键词： Reinforcement learning

Geometry-based data generation

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Lindenbaum, Ofir Stanley, Jay S. Wolf, Guy Krishnaswamy, Smita Department of Genetics Yale University New HavenCT United States Applied Mathematics Program Yale University New HavenCT United States Computational Biology & Bioinformatics Program Yale University New HavenCT United States Department of Computer Science Yale University New HavenCT United States

We propose a new type of generative model of high-dimensional data that learns a manifold geometry of the data, rather than density, and can generate points evenly along this manifold. This is in contrast to existing generative models that represent data density, and are strongly affected by noise and other artifacts of data collection. We demonstrate how this approach corrects sampling biases and artifacts, and improves several downstream data analysis tasks such as clustering and classification. Finally, we demonstrate that this approach is especially useful in biology where, despite the advent of single-cell technologies, rare subpopulations and gene-interaction relationships are affected by biased sampling. We show that SUGAR can generate hypothetical populations and reveal intrinsic patterns and mutual-information relationships between genes on a single cell dataset of hematopoiesis. Copyright © 2018, The Authors. All rights reserved.

关键词： Clustering algorithms

Physical model of discontinuity response in landslide application using geometry normalized electromagnetic system (GNES)

学校读者我要写书评

暂无评论

AIP Conference Proceedings 2020年第1期2221卷

作者： Muhammad Syukri Surbakti Bukhari Nazli Ismail Nasrullah Idris Muhammad Isa Elin Yusibani Zakaria Muhammad Nurman Mohd Zubir Mat Jafri 1Department of Physics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Jln. SyechAbdul Ra’uf No. 3 Darussalam 23111 Banda Aceh Aceh Indonesia 2Doctorate Program of Mathematics and Applied Science (DMAS) Postgraduate Program Universitas Syiah Kuala Banda Aceh 23111 Indonesia 3SMAN 2 Binjai Jalan Padang No. 8 Binjai 20722 Indonesia 4School of Physics UniversitiSains Malaysia Minden 11800 Penang Malaysia

The discontinuity in a fractured land in landslide application could be represented by the metal defects in the physical modeling that will usually reduce the mass of the metal. The scale factor n is important for interpreting the field data using the physical model data. In this physical modeling (n = 100), the anomaly targets are aluminum plates and aluminum plates with the discontinuities. It is assumed the nonconductive environment. In the free-air condition which has zero conductivity is become representative of this environment. In the zero conductivity, the secondary field from the medium is not presence. In this condition, there are no phase differences between transmitted electromagnetic fields and that was received by the receiver. The discontinuity in this term is any treatment or defect that causes disruption or leads to a reduction in response triggered by the eddy currents. The discontinuities used on the thin plates and flaws will interrupt or reduce the eddy current flow on the plate, thereby reducing the induced voltage on the receiving coil and increasing its effective impedance. This is the basis of eddy current measurement. The electromagnetic field response to a metal that has discontinuities will change the eddy current portion. The eddy current that changes, therefore, will change the second field so that the percent response (% Response) of the receiver in the Geometry Normalized Electromagnetic System (GNES) instrument will also change.

关键词：

Model of virus therapy and chemotherapy for cancer

学校读者我要写书评

暂无评论

IOP Conference Series: Earth and Environmental Science 2019年第1期364卷

作者： E Safitri T Tarmizi M Ramli S Wahyuni M Ikhwan Mathematics Graduate Study Program Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Mathematics Universitas Syiah Kuala Banda Aceh 23111 Indonesia Graduate School of Mathematics and Applied Science Universitas Syiah Kuala Banda Aceh 23111 Indonesia

This article discusses the mathematical model of changes in the number of cancer cells as a result of the intervention. Here the effect of combination treatment, in the form of virus injection and chemotherapy on tumor cells, is presented in detail. There are two different tumor cells, uninfected tumor cells and infected tumor cells. Model simulations with different parameters were performed for 700 d. The initial values for the population of virus-infected tumor cells are divided into two categories. The number of tumor cells injected with the virus is ½ (half) and all tumor cells that are not infected. Based on the simulation results, it was concluded that the more the number of tumor cells injected with the virus, the faster the decrease in the number of tumor cell populations. It was also concluded that the reduced population of tumor cells reduces the amount of chemotherapy concentration used.

关键词：

Optimal configurations in coverage control with polynomial costs ?

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Bopardikar, Shaunak D. Mehta, Dhagash Hauenstein, Jonathan D. United Technologies Research Center 411 Silver Lane East HartfordCT06118 United States Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556

We revisit the static coverage control problem for placement of vehicles with simple motion on the real line, under the assumption that the cost is a polynomial function of the locations of the vehicles. The main contribution of this paper is to demonstrate the use of tools from numerical algebraic geometry, in particular, a numerical polynomial homotopy continuation method that guarantees to find all solutions of polynomial equations, in order to characterize the global minima for the coverage control problem. The results are then compared against a classic distributed approach involving the use of Lloyd descent, which is known to converge only to a local minimum under certain technical conditions. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

Environment recognition based on images using bag-of-words 9

学校读者我要写书评

暂无评论

Environment recognition based on images using bag-of-words

9th International Joint Conference on computational Intelligence, IJCCI 2017

作者： Petraitis, Taurius Maskeliunas, Rytis Damaševičius, Robertas Polap, Dawid Woźniak, Marcin Gabryel, Marcin Department of Multimedia Engineering Kaunas University of Technology Kaunas Lithuania Institute of Mathematics Faculty of Applied Mathematics Silesian University of Technology Gliwice Poland Institute of Computational Intelligence Czestochowa University of Technology Czestochowa Poland

ISBN: (纸本)9789897582745

Object and scene recognition solutions have a wide application field from entertainment apps, and medical tools to security systems. In this paper, scene recognition methods and applications are analysed, and the Bag of Words (BoW), a local image feature based scene classification model is implemented. In the BoW model every picture is encoded by a bag of visual features, which shows the quantities of different visual features of an image, but disregards any spatial information. Five different feature detectors and two feature descriptors were analyzed and two best approaches were experimentally chosen as being most effective classifying images into eight outdoor categories: forced feature detection with a grid and description using SIFT descriptor, and feature detection with SURF and description with U-SURF. Support vector machines were used for classification. We also have found that for the task of scene recognition not just the distinct features which are found by common feature detectors are important, but also the features that are uninteresting for them. Indoor scenes were experimentally classified into five categories and worse results were achieved. This shows that indoor scene classification is a much harder task and a model which does not take into account any mid-level scene information like objects of the scene is not sufficient for the task. A computer application was written in order to demonstrate the algorithm, which allows training new classifiers with different parameters and using the trained classifiers to predict the classes of new images. © 2017 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Object recognition

Imaging the geometrical structure of complex symmetric molecules by above-threshold ionization spectrum in an ir+xuv laser field

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Zhou, Xu-Cong Shi, Shang Li, Fei Guo, Ying-Chun Yang, Yu-Jun Meng, Qing-Tian Chen, Jing Liu, Xiao-Jun Wang, Bingbing Laboratory of Optical Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China School of Physics and Electronics Shandong Normal University Jinan250358 China Department of Physics School of Physics and Electronics East China Normal University Shanghai200062 China Jilin University Insititute of Atomic and Molecular Physics Changchun130012 China Center for Applied Physics and Technology Peking University Hedps Beijing100871 China Institute of Applied Physics and Computational Mathematics Beijing100088 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan430071 China University of Chinese Academy of Sciences Beijing100049 China

Based on the frequency-domain theory, we put forward a method of imaging the complex symmetrical polyatomic molecules by using IR+XUV two-color laser fields. Although the wave function of a polyatomic molecule, such as SF6, is quite complex in momentum space, it can be simplified by several terms in the region of high value of momentum, where the destructive interference fringes from these terms carry the information of the molecular structure. In this work, we find that, since the XUV laser field may increases the kinetic energy of the photoelectron dramatically in the above-threshold ionization (ATI) process of a molecule in an IR+XUV two-color laser field, the information of the molecular structure can be obtained by analyzing the interference fringes of the ATI spectrum in the high-energy region, where the simplified wave function of the molecule plays a dominant role in this part of the ATI spectrum. This method provides a unique accessible route towards imaging polyatomic molecules from a frequency perspective. Copyright © 2019, The Authors. All rights reserved.

关键词： Wave functions

Geometric distance between positive definite matrices of different dimensions

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Lim, Lek-Heng Sepulchre, Rodolphe Ye, Ke Department of Statistics University of Chicago Computational and Applied Mathematics Initiative ChicagoIL60637 United States Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom KLMM Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

We show how the Riemannian distance on Sn++, the cone of n × n real symmetric or complex Hermitian positive definite matrices, may be used to naturally define a distance between two such matrices of different dimensions. Given that Sn++also parameterizes n-dimensional ellipsoids, and inner products on n, n×n covariance matrices of nondegenerate probability distributions, this gives us a natural way to define a geometric distance between a pair of such objects of different dimensions.15B48, 15A18, 51K99, 53C25 Copyright © 2018, The Authors. All rights reserved.

关键词： Covariance matrix

What is the dynamical regime of cerebral cortex?

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Ahmadian, Yashar Miller, Kenneth D. Institute of Neuroscience Departments of Biology and Mathematics University of Oregon OR United States Computational and Biological Learning Lab Department of Engineering University of Cambridge Cambridge United Kingdom Center for Theoretical Neuroscience Swartz Program in Theoretical Neuroscience Kavli Institute for Brain Science Dept. of Neuroscience College of Physicians and Surgeons Morton B. Zuckerman Mind Brain Behavior Institute Columbia University NY United States

Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron’s excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size to the factors that cancel, rather than tight, meaning that the net input is very small relative to the cancelling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas. Copyright © 2019, The Authors. All rights reserved.

关键词： Neurons