Joseph John

Abstract: Single neuron models are typical functional replica of the biological neuron that are derived using their individual and group responses in networks. In recent past, a lot of work in this area has produced advanced neuron models for both analog and binary data patterns. Popular among these are the higher-order neurons, fuzzy neurons and other polynomial neurons. In this paper, we propose a new neuron model based on a polynomial architecture. Instead of considering all the higher-order terms, a simple aggregation function is used. The aggregation function is considered as a product of linear functions in different dimensions of the space. The functional mapping capability of the proposed neuron model is demonstrated through some well known time series prediction problems and is compared with the standard multilayer neural network.

Abstract: A voltage source inverter is commonly used to supply a three-phase induction motor with variable frequency and variable voltage for variable speed applications. A suitable pulse width modulation (PWM) technique is employed to obtain the required output voltage in the line side of the inverter. The different methods for PWM generation can be broadly classified into Triangle comparison based PWM (TCPWM) and Space Vector based PWM (SVPWM). In TCPWM methods such as sine-triangle PWM, three phase reference modulating signals are compared against a common triangular carrier to generate the PWM signals for the three phases. In SVPWM methods, a revolving reference voltage vector is provided as voltage reference instead of three phase modulating waves. The magnitude and frequency of the fundamental component in the line side are controlled by the magnitude and frequency, respectively, of the reference vector. The highest possible peak phase fundamental is very less in sine triangle PWM when compared with space vector PWM. Space Vector Modulation (SVM) Technique has become the important PWM technique for three phase Voltage Source Inverters for the control of AC Induction, Brushless DC, Switched Reluctance and Permanent Magnet Synchronous Motors. The study of space vector modulation technique reveals that space vector modulation technique utilizes DC bus voltage more efficiently and generates less harmonic distortion when compared with Sinusoidal PWM (SPWM) technique. In this paper first a model for Space vector PWM is made and simulated using MATLAB/SIMULINK software and its performance is compared with Sinusoidal PWM. The simulation study reveals that Space vector PWM utilizes dc bus voltage more effectively and generates less THD when compared with sine PWM.

Abstract: An optical fiber, partially stripped of its cladding is shown to sense refractive index of a liquid in which the uncladded sensing region is immersed, to a high degree of precision and over a wide range of refractive index. The slope of sensor response is found to be non linear, can have either sign and can change sign at around refractive index of the fiber. The sensitivity of the sensor to refractive index change is dependent on cladding thickness and is a maximum at an intermediate thickness value. It is insensitive to the presence of absorption at the wavelength at which refractive index is being measured and to the chemical nature of the solute. Experiments designed to show that cladding modes are responsible for sensing are described.

Abstract: In the past few decades, surface plasmon resonance (SPR) phenomenon along with optical fiber technology has emerged as a major area of research among the fiber optic sensing research groups. On the other hand, lossy mode resonance (LMR) is another kind of resonance phenomenon recently exploited for fiber optic sensing. LMR has several advantages over the well established SPR such as, free from specific polarization of light and capability of multiple LMR generation. Since LMR phenomenon is nascent for researchers and there are no review articles available till date, in this paper, we review the LMR phenomenon in applications involving sensing and wavelength filtering.

Abstract: Optical wireless communication offers a viable alternative to radio frequency (RF) communication for indoor use and other applications where high performance links are needed These systems use infrared technology (IR), which has significant advantages over RF This paper presents a review of the most significant issues related to infrared communication technology, which will enable the realization of future high performance and cost-effective indoor optical wireless systems Several possible configurations for indoor optical wireless systems, modulation and multi-access techniques are presented as well as their advantages and limitations discussed

Abstract: In almost every scientific field, measurements are performed over time. These observations lead to a collection of organized data called time series. The purpose of time-series data mining is to try to extract all meaningful knowledge from the shape of data. Even if humans have a natural capacity to perform these tasks, it remains a complex problem for computers. In this article we intend to provide a survey of the techniques applied for time-series data mining. The first part is devoted to an overview of the tasks that have captured most of the interest of researchers. Considering that in most cases, time-series task relies on the same components for implementation, we divide the literature depending on these common aspects, namely representation techniques, distance measures, and indexing methods. The study of the relevant literature has been categorized for each individual aspects. Four types of robustness could then be formalized and any kind of distance could then be classified. Finally, the study submits various research trends and avenues that can be explored in the near future. We hope that this article can provide a broad and deep understanding of the time-series data mining research field.

Abstract: Balancing theoretical analysis and practical advice, this book describes all the underlying principles required to build high performance indoor optical wireless communication (OWC) systems based on visible and infrared light, alongside essential techniques for optimising systems by maximising throughput, reducing hardware complexity and measuring performance effectively. It provides a comprehensive analysis of information rate-, spectral- and power-efficiencies for single and multi-carrier transmission schemes, and a novel analysis of non-linear signal distortion, enabling the use of off-the-shelf LED technology. Other topics covered include cellular network throughput and coverage, static resource partitioning via dynamic interference-aware scheduling, realistic light propagation modelling, OFDM, optical MIMO transmission and nonlinearity modelling. Covering practical techniques for building indoor optical wireless cellular networks supporting multiple users and guidelines for 5G cellular system studies, in addition to physical layer issues, this is an indispensable resource for academic researchers, professional engineers and graduate students working in optical communications.

Abstract: Recently, visible light communication (VLC) technology has been gaining attention in both academia and industry This is driven by the progress of white light emitting diode (LED) technology for solid-state lighting (SSL) and the potential of simultaneously using such LEDs for illumination and indoor wireless data transmission This paper provides an overview about the technology and describes the physical layer implementation of a VLC system based on a modified version of the classical orthogonal frequency division multiplexing (OFDM) modulation technique Besides, the paper presents a hardware prototype for short-range broadcasting using a white LED lamp The OFDM system runs on DSP development boards Off-the-shelf 9 LEDs and a single photodiode (PD) are utilized to build the analog frontends The prototype allows investigating the influence of the electrical signal-to-noise ratio (SNR), constellation order, and channel coding on the bit-error performance Theoretical and experimental results on optical path loss show close match In this context, the influence of the LED beam angle on the horizontal coverage is highlighted

Abstract: An artificial neural network (ANN) that mimics the information processing mechanisms and procedures of neurons in human brains has achieved a great success in many fields, e.g., classification, prediction, and control. However, traditional ANNs suffer from many problems, such as the hard understanding problem, the slow and difficult training problems, and the difficulty to scale them up. These problems motivate us to develop a new dendritic neuron model (DNM) by considering the nonlinearity of synapses, not only for a better understanding of a biological neuronal system, but also for providing a more useful method for solving practical problems. To achieve its better performance for solving problems, six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are for the first time used to train it. The best combination of its user-defined parameters has been systemically investigated by using the Taguchi’s experimental design method. The experiments on 14 different problems involving classification, approximation, and prediction are conducted by using a multilayer perceptron and the proposed DNM. The results suggest that the proposed learning algorithms are effective and promising for training DNM and thus make DNM more powerful in solving classification, approximation, and prediction problems.