<p>The main aim of this paper is to present a novel control approach an induction machine (IM) using improved space vector modulation based direct torque (SVM-DTC) on the basis imaginary swapping instant technique. The strategy presented surmount drawbacks classical (DTC) and enhance dynamic performance motor. This method requires neither angle identification nor sector determination; use...

We present in this paper a novel dynamic learning method for classifying polyp candidate detections in Computed Tomographic Colonography (CTC) using an adaptation of the Least Square Support Vector Machine (LS-SVM). The proposed technique, called Weighted Proximal Support Vector Machines (WP-SVM), extends the offline capabilities of the SVM scheme to address practical CTC applications. Incremen...

A method based on Electrical Capacitance Tomography (ECT) and an improved Least Squares Support Vector Machine (LS-SVM) is proposed for void fraction measurement of oil-gas two-phase flow. In the modeling stage, to solve the two problems in LS-SVM, pruning skills are employed to make LS-SVM sparse and robust; then the Real-Coded Genetic Algorithm is introduced to solve the difficult problem...

This paper presents research on a permanent magnet synchronous motor (PMSM) by 5-level T-type inverter using linear quadratic regulator (LQR) control for speed control. The space vector modulation (SVM) structure the to improve quality of PMSM drive system is presented. aims successfully design state feedback controller in system. Simulink results are performed with different ranges and same to...

We consider the problem of text representation and categorization. Conventionally, a text document is represented by a vector in high dimensional space. Some learning algorithms are then applied in such a vector space for text categorization. Particularly, Support Vector Machine (SVM) has received a lot of attentions due to its effectiveness. In this paper, we propose a new classification algor...

The work investigates the use of multi dimensional histograms for segmentation of images of chronic wounds. We employ a Support Vector Machine (SVM) classifier for automatic extraction of wound region from an image. We show that the SVM classifier can generalize well on the difficult wound segmentation problem using only 3-D dimensional color histograms. We also show that color histograms of hi...

A widely-used tool for binary classification is the Support Vector Machine (SVM), a supervised learning technique that finds the “maximum margin” linear separator between the two classes. While SVMs have been well studied in the batch (offline) setting, there is considerably less work on the streaming (online) setting, which requires only a single pass over the data using sub-linear space. Exis...

This paper presents a study on the use of Support Vector Machines (SVMs) in classifying Malayalam Consonant – Vowel (CV) speech unit by comparing it to two other classification algorithms namely Artificial Neural Network (ANN) and k – Nearest Neighbourhood (k – NN). We extend SVM to combine many two class classifiers into multiclass classifier using Decision Directed Acyclic Graph (DDAG) algori...

Multilevel voltage source inverter has been recognized as an important alternative to the normal two level voltage source inverter, especially in high power application. Using multilevel technique, the output voltage amplitude is increased, switching devices stress is reduced and the overall harmonics profile is improved. Three presentable topologies can b considered for multilevel inverter (ML...