Reverberation suppression is a crucial problem in sonar communications. If the acoustic signal is radiated in the water as medium then the degradation is caused due to the reflection coming from surface, bottom, and volume of water. This paper presents a novel signal processing scheme that offers an improved solution in reducing the effect of interference caused due to reverberation. It is based on the combination of empirical mode decomposition (EMD) and adaptive boosting (AdaBoost) techniques. AdaBoost based EMD filtering technique is used for reverberation corrupted chirp signal to decrease the noisy components present in the received signal. An improvement in the probability of detection is achieved using the proposed algorithm. The simulation results are obtained for various reverberation times at various SNR levels.
The major motivation behind transistor scaling is the requirement for high-speed transistors with lower fabrication costs. When the fin thickness or breadth is smaller than 10 nm in a trigate FET, charges travel in a nonconfined fashion, resulting in the creation of energy subbands and causing volume inversion. In comparison to the carrier near a surface inversion layer, volume inversion experiences less interface scattering. In large-scale integrations, we have focused on developing a 3D model for surface potential by establishing the three-dimensional Poison’s equation and building a unique fin field-effect transistor (FinFET) structure. In this context, there is a growing interest in developing a low-cost, simple solution that combines plastic (polymer) as a substrate and organic materials to create electronics such as monitors and sensors. The research examines characteristics such as silicon width, oxide thickness, doping concentration, metal work-function about gate, and various surface potentials. For different circuit configurations, it also examines the DC and AC characteristics of the FinFET structure. A differential amplifier is built for RF application based on the device specifications. This work is aimed at improving the semiconductor design structure by adjusting device parameters, analyzing the results, establishing the best FinFET device preferences, and selecting an application for the optimized device. The 3D Poisson’s equation may be used to create an analytical model of a trigate nanosize FinFET, which can then be tested using a TCAD simulator. By constructing such a FinFET, we can structure and analyze various electrostatic parameters. To facilitate the creation of FinFET-based circuits, including product development, a novel transistor needs a creative device basis. The infrastructure’s support denotes a computationally advantageous numerical model that accurately depicts a FinFET. The work presents a compact model for semiconductor manufacturing that permits separate IC productions while achieving higher levels of excellence and using less power. The design outperforms the CMOS by 22.7% in gain, 31.48% in power consumption, and 12.72% in CMRR, while operating at a 5 GHz unity gain frequency.
Empirical Mode Decomposition (EMD) has been used effectively in the analysis of non-linear and non-stationary signals. As an application in Robust Signal Processing, in this paper we used this method to reduce noise from a corrupted signal which is obtained from a disaster environment. Conventional adaptive algorithms exhibit poor performance if we consider the signal from a real environment. In this paper it has been described how EMD can be applied for noise reduction by breaking the signal down into its components and how it can help in removing the noisy components from the original signal.
As a photocatalytic anode material, hematite (α-Fe2O3) is the most promising of the three iron oxides. The two other oxides are FeO, which is seldom available, and Fe3O4, which is found naturally in magnetite. There are both theoretical and experimental methods suggested for enhancing α-Fe2O3’s reactivity. First-principles calculations led to the design of two different doping concentrations of Al-doped α-Fe2O3(0001) structures and an Al2O3/Fe2O3 heterostructure in the (0001) plane. A detailed investigation of the state density and stability, band structure, local potentials, charge densities, and Bader charge analysis is presented in this paper. A reduction in energy was observed with the Al-doping of an α-Fe2O3(0001) surface slab. The increase in doping concentration favors the formation of doped systems, and Al’s presence in α-Fe2O3(0001) is an energetically favorable process. The work function increases by increasing the Al concentration on the surface compared to a pure α-Fe2O3(0001) slab. Based on Bader charge analysis and charge density difference studies, it appears that chemical bonding becomes ionic in Al-doped regions. We additionally investigate Al2O3/Fe2O3 interfaces by using first-principles calculations, aiming to shed light on their geometric structure and electronic properties. Al2O3/Fe2O3 interfaces are more thermodynamically favorable. The results of these studies suggest that the Al2O3/Fe2O3 heterojunction is a type-III broken-gap heterojunction rather than a staggered one. Additionally, oxygen evolution reaction (OER) electrocatalysts are discussed for Al-doped systems and the interface. As a result, the most favorable rate-limiting step in high-performance electrocatalysts relies on Al atom doping concentration to modulate the electronic and structural properties of Al-doped sites, while the concentration of active sites is increased and the OER rate is improved. Providing a basic understanding of the OER process at these interfaces, the discussion will be useful for exploring and developing better catalysts and device units.
For strongly correlated metal oxides, several density functional theories have been used to describe the electronic structure of bulk iron oxide (α‐Fe2O3) and corresponding surfaces, including GGA+U and hybrid functionals (HSE), but the accuracy of these methods is unclear for these metal oxides. In the present study, first‐principles simulations were carried out to examine the effects of a hybrid density functional on α‐Fe2O3 bulk and surface slabs. Further, by using GGA+U, van der Waals corrections and O2 over binding corrections were also examined. It has been found that HSE functionals with 17.5 % Fock exchange predict better properties than those with 12 % or 25 % exchange. Methodological studies indicate that GGA+U predicted zero‐bandgap surface slabs become semiconducting slabs at HSE, and that calculated bandgaps are dependent on the actual exchange addition percentage. Our studies also show that the surface energy and relative stability of different Fe2O3 terminations are less sensitive to the inclusion of dispersion terms. However, when accounting for the GGA‐error in O2 over‐binding, significant changes occur in the computed surface energies. Additionally, HSE06 functional was tested on MnO2(0001) and MnO2(110) surfaces. Both surfaces were identified as metallic by a PBE+U calculation, and an HSE06 analysis revealed a nonzero band gap.
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