Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 16 of 16 for “"Radial Basis Function Network"”.
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Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
… Recursive system identification based on neural network (NN) offers an alternative method for quadcopter dynamics modelling. Recursive learning algorithms, such as Constant Trace (CT) can be implemented to solve insufficient training data and over-fitting problems by developing a new model from …
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A Radial Basis Function Approach to a Color Image Classification Problem in a Real Time Industrial Application
In this thesis, we introduce a radial basis function network approach to solve a color image classification problem in a real time industrial application. Radial basis function networks are employed to classify the images of finished wooden parts in terms of their color and species. Other …
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A Fuzzy/Neural Approach to Cost Prediction with Small Data Sets
… method that is then put through an adaptive network based fuzzy inference system (ANFIS). The second method is a two stage system that uses various ANFIS with either single or multiple inputs for a cost estimate whose outputs are then put through a backpropagation trained neural network for …
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The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions
Neural networks have been applied to a number of problems over the past few years. One of the emerging applications of neural networks is adaptive communication channel equalisation. This area of research has become prominent due to the reformulation of the equalisation problem as a classification …
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Parameter estimation of induction motors using PWM inverters
… and (35]. The final algorithm tested uses a radial basis function network to approximate a function mapping from a time lag space consisting of the dq transformed stator currents to a space of machine electrical parameters. This algorithm is attractive because it is very easy to perform, …
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Characterizing the potential energy surface of two dimensional and bulk materials using high dimensional neural network potentials
… obtained using a feed-forward artificial neural network. An approximate Density Functional Theory method, Density Functional Tight Binding (DFTB+), is used to compute quantities required for the reference dataset. It is found that a network made up of linear activation functions in ænet is …
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INTELLIGENT FAULT DETECTION AND ISOLATION FOR PROTON EXCHANGE MEMBRANE FUEL CELL SYSTEMS
… in nonlinear processes using independent neural network models. In this approach, an independent neural network is used to model the proton exchange membrane fuel cell nonlinear systems using a multi-input multi-output structure. This research proposed the use of radial basis function network and …
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Signal decomposition for nonstationary processes
… or nonlinear signal are decomposed onto a set of basis functions, either in the phase space spanned by time-frequency coordinates as Gabor proposed, or in the phase space spanned by a set of derivatives of different degree as defined in physics. To deal with time-varying signals, a Multiresolution …
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Deep Learning-Driven Modeling of Dynamic Acoustic Sensing in Biommetic Soft Robotic Pinnae
… the development of deep regression neural networks capable of predicting the beampattern (acoustic radiation pattern) of a soft-robotic pinna as function of its actuator states. The pinna model geometry is derived from a tomographic scan of the right ear of the greater horseshoe bat …
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Dynamic recurrent neural networks for stable adaptive control of wing rock motion
… forces. In this thesis, dynamic recurrent RBF (Radial Basis Function) network control methodology is proposed to control the wing rock motion. The concept based on the properties of the Presiach hysteresis model is used in the design of dynamic neural networks. The structure and memory mechanism …
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An RBFN-based system for speaker-independent speech recognition
… compared. Phone recognition is performed using a radial basis function network (RBFN). Dynamic time warping (DTW) is used for word recognition. The TIMIT database is used to design and test the automatic speech recognition (ASR) system. Several feature sets using mel-scale filter bank (MSFB), …
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Intelligent energy management system - techniques and methods
… point genetic algorithm and artificial neural network based hybrid model for gaining accurate prediction of short-term load forecast has been developed. Adopting the new model is more accuracy than radial basis function network. Actual data has been used to test the proposed new method and it …
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Detection and Analysis of Molten Aluminium Cleanliness Using a Pulsed Ultrasound System
… vector machine, multi-layer perceptron and a radial basis function network. The hyperparameters are tuned using 10- fold repeated cross-validation. The multi-layer perceptron offers the best performance in all cases. For determining the quality outcome of a cast (passed or failed), all the …
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EEG Feature Extraction and Pattern Recognition Based on Chaotic Systems
… a novel extension of ANN(Artificial Neural Networks) based modelling for chaotic systems. The Rossler’s and Chua’s systems are used for the study. A NARX (Nonlinear Autoregressive Exogenous) model is proposed to train bifurcation patterns of chaotic systems and performance of various NARX …
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Teleoperation System for Autonomous Vehicles
… to alleviate the impact of signal latency. And Radial Basis Function Networks (RBFN) are employed to effectively manage the uncertain nonlinear dynamics of the vehicle. Subsequently, a saliency-based object detection (OD) algorithm, named SalienDet, is proposed to identify objects not present in …
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Incremental learning for large-scale stream data and its application to cybersecurity
… and basic theories on Resource Allocating Network (RAN) and conventional data selection method are discussed in this chapter. Besides that, the overview of this dissertation is also elaborated in this chapter. In Chapter 2, we propose a new algorithm based on incremental Radial Basis …