Rigorous comparison of parabolically tapered and conventional multimode-interference-based 3-dB power splitters in InGaAsP/InP waveguides

Design issues such as optical transmission, interference mechanisms, the splitting ratio, the polarization dependence, and the fabrication tolerances of a compact parabolically tapered multimode-interference (MMI)-based 3-dB power splitter on an InP-based deeply etched ridge waveguide, by use of the finite-element-based beam-propagation method, are presented. The benefits and drawbacks of the use of the tapered structure, in comparison with an untapered MMI-based 3-dB splitter, have also been investigated.     

Efficient multiresolution time-domain analysis of arbitrarily shaped photonic devices

A multiresolution time-domain (MRTD) technique is proposed and applied to the analysis of arbitrarily shaped photonic devices. The suggested method implements the multiresolution analysis in the context of method-of-moments for the solution of Maxwell?s equations. To improve the capabilities of the proposed method, the uniaxial perfectly matched layers absorber for the MRTD is rigorously incorporated and better performance is reported over the conventional finite-difference time-domain. Various numerical examples demonstrate the stability and numerical precision of the suggested MRTD method for both linear and nonlinear applications. Moreover, the application of the suggested MRTD scheme for the design of a photonic crystal-based optical wavelength filter and for the analysis of a frequency converter is presented.     

Full vectorial finite-element-based imaginary distance beampropagation solution of complex modes in optical waveguides

In this paper, we address accurate computation of complex propagation constants and field distributions of different modes, in general, lossless and lossy optical dielectric waveguides. Using the vector finite-element formulation of the beam propagation method combined with the imaginary distance propagation technique, sequence of both the guided and leaky modes can be accurately calculated. To show the versatility and numerical precision of the proposed technique, we compute the modes of three different three-dimensional (3-D) waveguide structures and compare the results against those of other, different, vector formulations. Further, we present the design of a higher order mode filtering device, based on a 3-D leaky mode optical waveguide     

Full vectorial finite-element solution of nonlinear bistable optical waveguides

The accurate computation of the propagation constants and field distributions of different modes in nonlinear optical dielectric waveguides is addressed in this paper. Using the vector finite-element formulation of the beam propagation method, combined with the imaginary distance propagation technique, both linear and nonlinear modes can be accurately calculated. The proposed technique is applied to obtain the fundamental TE nonlinear mode of a strip-loaded waveguide, and the excellent agreement seen with published results shows its high numerical precision.     

Novel finite element analysis of optical waveguide discontinuity problems

In this paper, a novel finite-element method (FEM) to rigorously and efficiently solve the optical waveguide discontinuity problems is presented. Instead of performing the time-consuming modal solutions on both discontinuity sides, the square root of the characteristic matrix is efficiently approximated using Taylor's series expansion, and then the interface boundary conditions are enforced at the discontinuity plane to solve for the reflected and transmitted fields. The high numerical precision and effectiveness of the proposed method is demonstrated through the analysis of various discontinuity problems, and the excellent agreement of the results obtained using the present finite element method and those obtained using other rigorous approaches in the literature.     

Intelligent Biomedical Electrocardiogram Signal Processing for Cardiovascular Disease Diagnosis

Automatic biomedical signal recognition is an important process for several disease diagnoses. Particularly, Electrocardiogram (ECG) is commonly used to identify cardiovascular diseases. The professionals can determine the existence of cardiovascular diseases using the morphological patterns of the ECG signals. In order to raise the diagnostic accuracy and reduce the diagnostic time, automated computer aided diagnosis model is necessary. With the advancements of artificial intelligence (AI) techniques, large quantity of biomedical datasets can be easily examined for decision making. In this aspect, this paper presents an intelligent biomedical ECG signal processing (IBECG-SP) technique for CVD diagnosis. The proposed IBECG-SP technique examines the ECG signals for decision making. In addition, gated recurrent unit (GRU) model is used for the feature extraction of the ECG signals. Moreover, earthworm optimization (EWO) algorithm is utilized to optimally tune the hyperparameters of the GRU model. Lastly, softmax classifier is employed to allot appropriate class labels to the applied ECG signals. For examining the enhanced outcomes of the proposed IBECG-SP technique, an extensive simulation analysis take place on the PTB-XL database. The experimental results portrayed the supremacy of the IBECG-SP technique over the recent state of art techniques.     

Numerical analysis of bent waveguides: bending loss, transmission loss, mode coupling, and polarization coupling

A rigorous, full-vectorial and computationally efficient finite-element-based modal solution, together with junction analysis and beam propagation approaches have been used to study bending loss, transition loss, mode coupling, and polarization coupling in bent optical waveguides. The waveguide offset and their widths have been optimized to reduce the transition loss and the mode beating.     

New full-vectorial numerically efficient propagation algorithmbased on the finite element method

A new full-vectorial beam propagation algorithm based on the versatile finite element method, in order to accurately characterize three-dimensional (3-D) optical guided-wave devices, is presented. The computationally efficient formulation is based on the two transverse components of the magnetic field without destroying the sparsity of the matrix equation. The robust perfectly matched layer (PML) boundary condition is incorporated into the formulation so as to effectively absorb the unwanted radiation out of the computational domain. The efficiency and precision of the proposed full-vectorial propagation approach is demonstrated through the analysis of single optical waveguide, directional couplers, and electrooptic modulator     

Design and characterization of compact single-section passivepolarization rotator

In this paper an improved design for a short and low-loss polarization rotator is proposed, consisting of a single-section asymmetrical waveguide butt-coupled between two standard rib waveguides. At a wavelength of 1.55 μm, nearly 100% polarization conversion ratio is obtained, with a relatively short (320 μm) device length and an extremely low 0.5 dB total insertion loss. The simulation results are obtained using the full vectorial finite-element-based beam propagation, the junction analysis, and the modal solution approaches     

Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

With new developments experienced in Internet of Things (IoT), wearable, and sensing technology, the value of healthcare services has enhanced. This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare. Bio-medical Electrocardiogram (ECG) signals are generally utilized in examination and diagnosis of Cardiovascular Diseases (CVDs) since it is quick and non-invasive in nature. Due to increasing number of patients in recent years, the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients. In such scenario computer-assisted automated diagnostic tools are important for classification of ECG signals. The current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECG Signal Classification (IBADL-BECGC) approach. To accomplish this, the proposed IBADL-BECGC model initially pre-processes the input signals. Besides, IBADL-BECGC model applies NasNet model to derive the features from test ECG signals. In addition, Improved Bat Algorithm (IBA) is employed to optimally fine-tune the hyperparameters related to NasNet approach. Finally, Extreme Learning Machine (ELM) classification algorithm is executed to perform ECG classification method. The presented IBADL-BECGC model was experimentally validated utilizing benchmark dataset. The comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.