检索结果-内蒙古大学图书馆

Simple agent-based dynamical system models for efficient financial markets: Theory and examples

JOURNAL OF MATHEMATICAL ECONOMICS 2017年 69卷 38-53页

作者： Immonen, Eero Turku Univ Appl Sci Fac Technol Environm & Business Sepankatu 1 Turku 20700 Finland

We propose an agent-based framework, based on simple piecewise linear time-invariant continuous-time dynamical systems models, as a means for describing efficient financial markets. We show by examples that many of the common agent-specific trading strategies occurring in the academic literature, including chartists and fundamentalists of various kinds, can be described in the proposed framework. We present definitions for weak and strong market efficiency and provide necessary and sufficient conditions for them to hold. We present minimal examples of strongly and weakly efficient markets to show that these concepts are natural and easy to satisfy in agent-based models, and that the models can reproduce both statistical and behavioral stylized facts of real markets. We provide examples to demonstrate that the framework can be extended for agents with delays in information processing, as well as for agents with time-varying strategies and for nonlinear market impact functions. We also provide a counterexample to show that the proposed market efficiency concepts may require modification in generalizations for nonlinear trading strategies. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Minimal agent-based models linear dynamical system Efficient Market Hypothesis Adaptive Market Hypothesis Feedback

来源：评论

学校读者我要写书评

暂无评论

Underwater Non-Rigid 3D Shape Reconstruction via Structure from Motion for Fish Ethology Research

Underwater Non-Rigid 3D Shape Reconstruction via Structure f...

引用

MTS/IEEE Oceans Conference

作者： Che, Renzheng Xu, Xiao Nian, Rui He, Bo Chen, Meimei Zhang, Cheng Lendasse, Amaury Ocean Univ China Sch Informat Sci & Engn 238 Songling Rd Qingdao Peoples R China Qingdao Univ Sci & Technol Qingdao Peoples R China Univ Iowa Dept Mech & Ind Engn Iowa City IA 52242 USA Univ Iowa Iowa Informat Initiat Iowa City IA 52242 USA Arcada Univ Appl Sci Helsinki 00550 Finland

ISBN: (纸本)9781509015375

In this paper, we try to develop a general framework of 3D shape reconstruction strategy with extremely rare point cloud extracted for fish ethology research. Particle filter is first taken to focus on fish trajectory tracking from monocular video sequence. The Speeded Up Robust Features (SURF) technique will be adopted to match the same tracking fish across the overlapping view fields with more stable and accurate features. Non-rigid 3D shape reconstruction will be finally developed with the help of expectation maximization (EM) model and linear dynamical system (LDS). It is shown from our simulation experiment that the developed scheme of this paper achieves consistent performance improvements over non-rigid 3D shape reconstruction for fish ethology research.

关键词： non-rigid 3D shape reconstruction Structure from motion expectation maximization linear dynamical system

来源：评论

学校读者我要写书评

暂无评论

REALISTIC HUMAN ACTION RECOGNITION: WHEN CNNS MEET LDS

REALISTIC HUMAN ACTION RECOGNITION: WHEN CNNS MEET LDS

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhang, Lei Feng, Yangyang Xiang, Xuezhi Zhen, Xiantong Harbin Engn Univ Coll Informat & Commun Engn Harbin Heilongjiang Peoples R China Univ Western Ontario Dept Med Biophys London ON Canada

ISBN: (纸本)9781509041176

In this paper, we proposed new framework for human action representation, which leverages the strengths of convolutional neural networks (CNNs) and the linear dynamical system (LDS) to represent both spatial and temporal structures of actions in videos. We make two principal contributions: first, we incorporate image-trained CNNs to detect action clip concepts, which takes advantage of different levels of information by combining the two layers in CNNs trained from images;Second, we further propose adopting a linear dynamical system (LDS) to model the relationships between these clip concepts, which captures temporal structures of actions. We have applied the proposed method on two challenging realistic benchmark datasets, and our method achieves high performance up to 86.16% on the YouTube and 82.76% UCF50 datasets, which largely outperforms most of the state-of-the-art algorithms with more sophisticated techniques.

关键词： Deep learning Image-trained CNNs linear dynamical system Concept confidence

来源：评论

学校读者我要写书评

暂无评论

A Unified Approach to Network Anomaly Detection 2

A Unified Approach to Network Anomaly Detection

引用

IEEE International Conference on Big Data

作者： Babaie, Tahereh Chawla, Sanjay Ardon, Sebastien Yu, Yue Univ Sydney Sch IT Sydney NSW Australia NICTA ATP Res Lab Alexandria NSW Australia

ISBN: (纸本)9781479956661

This paper presents a unified approach for the detection of network anomalies. Current state of the art methods are often able to detect one class of anomalies at the cost of others. Our approach is based on using a linear dynamical system (LDS) to model network traffic. An LDS is equivalent to Hidden Markov Model (HMM) for continuous-valued data and can be computed using incremental methods to manage high-throughput (volume) and velocity that characterizes Big Data. Detailed experiments on synthetic and real network traces shows a significant improvement in detection capability over competing approaches. In the process we also address the issue of robustness of network anomaly detection systems in a principled fashion.

关键词： Big Data computer network security hidden Markov models HMM LDS continuous-valued data hidden Markov model linear dynamical system network anomaly detection network traffic Computer crime Correlation Hidden Markov models IP networks Kalman filters Ports (Computers) Robustness

来源：评论

学校读者我要写书评

暂无评论

Feature Ranking in Dynamic Texture Clustering 12

Feature Ranking in Dynamic Texture Clustering

引用

12th Conference on Computer and Robot Vision (CRV)

作者： Thanh Minh Nguyen Wu, Q. M. Jonathan Mukherjee, Dibyendu Univ Windsor Dept Elect & Comp Engn 401 Sunset Ave Windsor ON N9B 3P4 Canada

ISBN: (纸本)9781479919864

The dynamic texture clustering over space and time, which considers a video as a sample from a linear dynamical system, has recently received great attention. While there exist many algorithms for time-varying characteristics and phenomena clustering, an important and challenging issue arising from these studies concerns is that how to compare the importance of each feature, and which features of the data should be used for time-varying clustering. In view of the aforementioned observations, a new unsupervised feature ranking for dynamic texture clustering is proposed in this paper. Different from previous works, where the selection criteria are often used to identify relevant features, our method has an ability to score relevant features, and allow us to evaluate the importance of each feature. Also, it is intuitively appealing, avoiding any combinatorial search. Numerical experiments on various time-varying characteristics and phenomena demonstrate the accuracy and effectiveness of the proposed method.

关键词： Dynamic Texture unsupervised feature ranking linear dynamical system segmentation

来源：评论

学校读者我要写书评

暂无评论

Inverse Mathematical Modelling of Hexadecane Disintegration Reaction with Cooperative Multi-objective Genetic Algorithms 14th

Inverse Mathematical Modelling of Hexadecane Disintegration ...

引用

14th International Conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Ryzhikov, Ivan Brester, Christina Semenkin, Eugene Reshetnev Siberian State Univ Sci & Technol Krasnoyarskiy Rabochyi Ave 31 Krasnoyarsk 660037 Russia

ISBN: (纸本)9783030112929;9783030112912

In this paper, we consider the inverse mathematical modelling problem for linear dynamic systems with multiple inputs and multiple outputs. The problem of this kind appears in chemical disintegration reactions and determines product concentration changing. In general case of dynamical system modelling, one needs to identify its parameters and initial values. The reason for this is the fact that a dynamical system output is a reaction on some input function and it depends on the initial state of the system. This means that changing initial values would cause parameter changing and vice versa. At the same time, statistical approximation of initial values does not give us a reliable result because in most of the cases data is noisy and flat. To provide simultaneous estimation of parameters and initial values we propose an approach based on the reduction of the inverse modelling problem to a two-criterion extremum problem and then approximating the Pareto front with specific evolution-based algorithms. Different algorithms, such as SPEA-II, PICEA-g and NSGA-2, were applied to solve the reduced multi-objective black-box optimization problem as well as their heterogeneous and homogeneous cooperations. We compared performance of these algorithms on solving inverse modelling problems for concentrations of hexadecane disintegration reaction products in case of diffusion and static reactions. On the base of numerical experiments, we provided the analysis of algorithm performances.

关键词： Inverse mathematical modelling linear dynamical system Identification Multi-objective optimization Evolution-based algorithms

来源：评论

学校读者我要写书评

暂无评论

LEARNING SILHOUETTE DYNAMICS FOR HUMAN ACTION RECOGNITION

LEARNING SILHOUETTE DYNAMICS FOR HUMAN ACTION RECOGNITION

引用

20th IEEE International Conference on Image Processing (ICIP)

作者： Luo, Guan Hu, Weiming Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China

ISBN: (纸本)9781479923410

In this paper, we address the problem of recognizing human actions with motion dynamics alone. For this purpose, we propose to use silhouette sequences to represent the human actions by discarding the appearance information, and then model the sequences with linear dynamical systems (LDSs). Recognition is achieved by directly comparing the distance between LDSs, rather than resorting to complex Bayesian learning and inference. In particular, we introduce an efficient optimization method to learn robust LDSs, and develop a shift invariant distance metric to measure the similarity on the LDSs space. We evaluate our approach on the human action data set and achieve comparable results.

关键词： Action recognition linear dynamical system silhouette similarity measurement

来源：评论

学校读者我要写书评

暂无评论

Context-Based Pedestrian Path Prediction

Context-Based Pedestrian Path Prediction

引用

13th European Conference on Computer Vision (ECCV)

作者： Kooij, Julian Francisco Pieter Schneider, Nicolas Flohr, Fabian Gavrila, Dariu M. Daimler R&D Environm Percept Ulm Germany

ISBN: (纸本)9783319105994;9783319105987

We present a novel Dynamic Bayesian Network for pedestrian path prediction in the intelligent vehicle domain. The model incorporates the pedestrian situational awareness, situation criticality and spatial layout of the environment as latent states on top of a Switching linear dynamical system (SLDS) to anticipate changes in the pedestrian dynamics. Using computer vision, situational awareness is assessed by the pedestrian head orientation, situation criticality by the distance between vehicle and pedestrian at the expected point of closest approach, and spatial layout by the distance of the pedestrian to the curbside. Our particular scenario is that of a crossing pedestrian, who might stop or continue walking at the curb. In experiments using stereo vision data obtained from a vehicle, we demonstrate that the proposed approach results in more accurate path prediction than only SLDS, at the relevant short time horizon (1 s), and slightly outperforms a computationally more demanding state-of-the-art method.

关键词： intelligent vehicles path prediction situational awareness visual focus of attention Dynamic Bayesian Network linear dynamical system

来源：评论

学校读者我要写书评

暂无评论

Speech Estimation in Non-Stationary Noise Environments Using Timing Structures between Mouth Movements and Sound Signals

Speech Estimation in Non-Stationary Noise Environments Using...

引用

11th Annual Conference of the International-Speech-Communication-Association 2010

作者： Kawashima, Hiroaki Horii, Yu Matsuyama, Takashi Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

ISBN: (纸本)9781617821233

A variety of methods for audio-visual integration, which integrate audio and visual information at the level of either features, states, or classifier outputs, have been proposed for the purpose of robust speech recognition. However, these methods do not always fully utilize auditory information when the signal-to-noise ratio becomes low. In this paper, we propose a novel approach to estimate speech signal in noise environments. The key idea behind this approach is to exploit clean speech candidates generated by using timing structures between mouth movements and sound signals. We first extract a pair of feature sequences of media signals and segment each sequence into temporal intervals. Then, we construct a cross-media timing-structure model of human speech by learning the temporal relations of overlapping intervals. Based on the learned model, we generate clean speech candidates from the observed mouth movements.

关键词： multimodal non-stationary noise timing linear dynamical system particle filtering

来源：评论

学校读者我要写书评

暂无评论

Multi-sensor physical activity recognition in free-living

Multi-sensor physical activity recognition in free-living

引用

ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)

作者： Ellis, Katherine Kerr, Jacqueline Godbole, Suneeta Lanckriet, Gert Univ Calif San Diego Elect & Comp Engn 9500 Gilman Dr La Jolla CA 92023 USA Univ Calif San Diego Family & Prevent Med La Jolla CA 92023 USA

ISBN: (纸本)9781450330473

Physical activity monitoring in free-living populations has many applications for public health research, weight-loss interventions, context-aware recommendation systems and assistive technologies. We present a system for physical activity recognition that is learned from a free-living dataset of 40 women who wore multiple sensors for seven days. The multi-level classification system first learns low-level codebook representations for each sensor and uses a random forest classifier to produce minute-level probabilities for each activity class. Then a higher-level HMM layer learns patterns of transitions and durations of activities over time to smooth the minute-level predictions.

关键词： Activity recognition linear dynamical system Codebook Accelerometer GPS

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：