Adaptive non linear system identification and channel equalization usinf functional link artificial neural network

In system theory, characterization and identification are fundamental problems. When the plant behavior is completely unknown, it may be characterized using certain model and then, its identification may be carried out with some artificial neural networks(ANN) like multilayer perceptron(MLP) or functional link artificial neural network(FLANN) using some learning rules such as back propagation (BP) algorithm. They offer flexibility, adaptability and versatility, so that a variety of approaches may be used to meet a specific goal, depending upon the circumstances and the requirements of the design specifications. The primary aim of the present thesis is to provide a framework for the systematic design of adaptation laws for nonlinear system identification and channel equalization. While constructing an artificial neural network the designer is often faced with the problem of choosing a network of the right size for the task. The advantages of using a smaller neural network are cheaper cost of computation and better generalization ability. However, a network which is too small may never solve the problem, while a larger network may even have the advantage of a faster learning rate. Thus it makes sense to start with a large network and then reduce its size. For this reason a Genetic Algorithm (GA) based pruning strategy is reported. GA is based upon the process of natural selection and does not require error gradient statistics. As a consequence, a GA is able to find a global error minimum. Transmission bandwidth is one of the most precious resources in digital communication systems. Communication channels are usually modeled as band-limited linear finite impulse response (FIR) filters with low pass frequency response. When the amplitude and the envelope delay response are not constant within the bandwidth of the filter, the channel distorts the transmitted signal causing intersymbol interference (ISI). The addition of noise during propagation also degrades the quality of the received signal. All the signal processing methods used at the receiver's end to compensate the introduced channel distortion and recover the transmitted symbols are referred as channel equalization techniques.When the nonlinearity associated with the system or the channel is more the number of branches in FLANN increases even some cases give poor performance. To decrease the number of branches and increase the performance a two stage FLANN called cascaded FLANN (CFLANN) is proposed.This thesis presents a comprehensive study covering artificial neural network (ANN) implementation for nonlinear system identification and channel equalization. Three ANN structures, MLP, FLANN, CFLANN and their conventional gradient-descent training methods are extensively studied. Simulation results demonstrate that FLANN and CFLANN methods are directly applicable for a large class of nonlinear control systems and communication problems

Development of Radar Pulse Compression Techniques Using Computational Intelligence Tools

Pulse compression techniques are used in radar systems to avail the benefits of large range detection capability of long duration pulse and high range resolution capability of short duration pulse. In these techniques a long duration pulse is used which is either phase or frequency modulated before transmission and the received signal is passed through a filter to accumulate the energy into a short pulse. Usually, a matched filter is used for pulse compression to achieve high signal-to-noise ratio (SNR). However, the matched filter output i.e. autocorrelation function (ACF) of a modulated signal is associated with range sidelobes along with the mainlobe. These sidelobes are unwanted outputs from the pulse compression filter and may mask a weaker target which is present nearer to a stronger target. Hence, these sidelobes affect the performance of the radar detection system. In this thesis, few investigations have been made to reduce the range sidelobes using computational intelligence techniques so as to improve the performance of radar detection system. In phase coded signals a long pulse is divided into a number of sub pulses each of which is assigned with a phase value. The phase assignment should be such that the ACF of the phase coded signal attain lower sidelobes. A multiobjective evolutionary approach is proposed to assign the phase values in the biphase code so as to achieve low sidelobes. Basically, for a particular length of code mismatch filter is preferred over matched filter to get better peak to sidelobe ratio (PSR). Recurrent neural network (RNN) and recurrent radial basis function (RRBF) structures are proposed as mismatch filters to achieve better PSR values under various noise conditions, Doppler shift and multiple target environment

Effect of Ti underlayer thickness on the magnetic anisotropy of TbFe thin films

In this study, we address the impact of Ti underlayer thickness (UL: 0-40 nm) on the structural, magnetic, and microscopic properties of TbFe thin films. The structural analysis confirmed the intermixing at interfaces of the Ti and TbFe layer with the increment of UL thicknesses. Out-of-plane (OOP) coercivity (Hc), and saturation field (Hs) gradually increased with an increase in UL thickness regardless of interface mixing. For UL = 10 nm, the domain contrast and OOP stray field strength were enhanced, which may be due to the extent of d-d hybridization dominated over the influence of interfacial roughness. While for UL = 20, and 40 nm, the extent of interfacial roughness dominated the hybridization effects and as a result, stray fields deteriorated. By placing UL of 20 nm, Hc increased by nearly 6 times more than the bare TbFe system. So, we observe a state with high OOP Hc combined with nearly zero OOP stray fields that are found to co-exist in the sample. The magnetization reversal studies on a large area reveal domain nucleation followed by domain-wall motion in all the films. The idea of tuning magnetic properties by varying thicknesses of Ti UL may useful in spintronics applications.Comment: 6 pages, 5 figure

An experimental investigation on metallurgical and corrosion behavior of atmospheric plasma sprayed Stellite 6 powder on AISI 304 stainless steel

An experimental investigation was undertaken to study the Cobalt-based Stellite 6, powder deposited on SS 304 stainless steel substrate without any intermittent layer using an atmospheric plasma spray deposition process by varying the thickness of coating in the range of 74 µm, 128 µm, and 215 µm. The effect of coating thickness on metallurgical properties and corrosion resistance behavior was investigated. Optical microscopy, Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray Spectroscopy (EDS) were employed to study the morphology of Stellite 6 coating. X-Ray Diffraction was used for structural analysis and to identify the phase formation. It was observed that the sample with 128 µm coating thickness provides the best result concerning microhardness and microstructure characteristics whereas the sample with 215 µm coating thickness provides the best corrosion resistance property. The reasons for the deviation were investigated and the factors responsible for the deviation were assigned in this investigation

PRINCIPAL COMPONENT ANALYSIS OF MORPHOLOGICAL TRAITS OF HARINGHATA BLACK CHICKENS IN AN ORGANIZED FARM

The present study was conducted to explore the relationship among body measurement in Haringhata Black Chicken using principal component analysis keeping in view of identifying those components that define body conformation in this breed. The parameters body weight, breast girth, keel length, body length, ornithological measurement, beak length, beak width and back length were recorded and evaluated on 22nd week of age of 113 Chicken. The data showed that the mean body weight was 963 gm and the body measurements were 23.96 cm, 9.80 cm, 59.27 cm, 51.14 cm, 2.38 cm, 1.40 cm and 9.79 cm for breast girth, keel length, body length, ornithological measurement, beak length, beak width and back length at 22nd week of age, respectively. The highest correlation was obtained between body weight and body length (r = 0.86), body length and ornithological measurement (r = 0.86) while correlation between beak width and ornithological measurement (r = 0.26) was observed to be the lowest. Extracted two principal components PC 1 and PC 2 explained 75.70 % of the total variation in the original variables. The first principal component (PC 1) had the largest share (60.02 %) of the total variance and had high positive loadings on body weight (0.93), body length (0.89), ornithological measurement (0.88), breast girth (0.86) and keel length (0.85) while PC 2 shared only 15.68% of the total variance with high positive loadings on beak width (0.75) and beak length (0.68). Therefore, PC1 may be used as selection criteria for improving body weight of indigenous Haringhata Black chicken

Challenges in QCD matter physics - The Compressed Baryonic Matter experiment at FAIR

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sqrt(s_NN) = 2.7 - 4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (mu_B > 500 MeV), effects of chiral symmetry, and the equation-of-state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2022, in the context of the worldwide efforts to explore high-density QCD matter.Comment: 15 pages, 11 figures. Published in European Physical Journal

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

Peer reviewe