Multiple Local Models for System Identification Using Vector Quantization Algorithms
نویسندگان
چکیده
We introduce a novel method to build multiple local regression models based on the prototype vectors of the SOM network and other well-known vector quantization (VQ) algorithms. The resulting models are evaluated in the task of identifying the inverse dynamics of a heat exchanger data set. Additionally, we evaluate through statistical hypothesis testing the influence of the VQ algorithm on the performance of the local model. Simulation results demonstrate that the proposed method consistently outperforms previous MLPand SOM-based approaches for system identification.
منابع مشابه
On building local models for inverse system identification with vector quantization algorithms
In this paper we provide a comprehensive performance evaluation of vector quantization (VQ) algorithms as building blocks for designing local models for inverse system identification. We describe how VQ algorithms can be used for learning compact representations of the task of interest from available input–output time series data and how this representation can be used to build local maps that ...
متن کاملIdentification of Dynamical Systems Using GMM with VQ Initialization
We are using Gaussian Mixture Models (GMM) as a tool to construct local mappings of nonlinear Multi-Input Multi-Output (MIMO) systems. In this work we combine the advantages of GMM with the Kalman filter. To improve the accuracy of the local linear mappings in a potentially large dimensional state space, we propose to initialize the GMM parameters with Vector Quantization (VQ) or its more parsi...
متن کاملSystem Identification using Delaunay Tessellation of Self-Organizing Maps
The Self-Organizing Map (SOM) is a vector quantization method which places prototype vectors on a regular low-dimensional grid in an ordered fashion. A new method to obtain piecewise linear models of dynamic processes is presented. The operating regimes of the local linear models are obtained by the Delaunay tessellation of the codebook of the SOM. The proposed technique is demonstrated by mean...
متن کاملFuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition
In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...
متن کاملMagnetic Calibration of Three-Axis Strapdown Magnetometers for Applications in Mems Attitude-Heading Reference Systems
In a strapdown magnetic compass, heading angle is estimated using the Earth's magnetic field measured by Three-Axis Magnetometers (TAM). However, due to several inevitable errors in the magnetic system, such as sensitivity errors, non-orthogonal and misalignment errors, hard iron and soft iron errors, measurement noises and local magnetic fields, there are large error between the magnetometers'...
متن کامل