A Miniaturized wide Stopband Low-pass Filter using T and Modified L Shapes Resonators

A new structure of microstrip-based low-pass filter with wide stopband and sharp roll-off is introduced, in this paper. In the proposed topology, resonators with T and modified L Shapes have been used. To improve the suppression factor and relative stopband bandwidth, the second resonator has been added to the first resonator. The designed filter has been fabricated on a 20 mm thickness RO4003 substrate, which has a loss tangent of 0.0021 and a relative dielectric constant equal to 3.38. All parameters including roll of rate, stopband, bandwidth, return loss, insertion loss, and figure of merit have significant coefficients. Simulation has been ran using advanced design system software. The 3dB cutoff frequency is appropriate. The value of the insertion loss parameter is <0.1 dB and the S11 parameter is −22 dB at this point. The stopband is extended from 2.42 up to 24 GHz, which shows an ultra-stopband. The results of the simulation and experiment are almost similar, which indicates a proper performance of the designed structure

An Ultra-wideband Low-power Low-noise Amplifier Linearized by Adjusted Derivative Superposition and Feedback Techniques

Ultra-wideband (UWB) applications require low-power and low-noise amplifiers (LNAs) that can operate over a wide frequency range. However, conventional LNAs often suffer from poor linearity and high-power consumption. This research work proposes a novel LNA design that uses the adjusted derivative superposition (DS) technique and feedback to improve the linearity and reduce the power consumption of UWB LNAs. The DS technique enhances the third-order intermodulation (IM3) cancellation by adjusting the bias currents of the transistors, whereas the feedback improves the stability and input matching of the LNA. The LNA is implemented using a degenerated common source topology in a 180 nm standard CMOS technology. The simulation results show that the LNA achieves a power gain of 10–12.2 dB, an input third-order intercept point (IIP3) of about 12 dBm, and a noise figure of less than 2.5 dB over the UWB frequency band of 3.1–10.6 GHz. The input reflection coefficient is less than -10 dB, and the power consumption is 11.6 mW with a 1.5 V power supply. The designed LNA offers a novel and innovative solution for UWB applications that significantly improve the performance and efficiency of UWB LNAs whereas reducing the cost and complexity of implementation

Compact Microstrip Low-pass Filter with Wide Stop-band Using P-Shaped Resonator

Abstract This paper, a compact low-pass filter (LPF) with an Elliptic function response using P-shaped resonators is presented. The LPF with simple structure results in the low insertion loss less than 0.1 dB and high return loss better than 20 dB, in the pass-band. The proposed filter with a −3 dB cutoff frequency of 2.61 GHz is fabricated and measured. The measured results show that the proposed LPF has significant advantages such as a wide stop-band from 2.9 GHz to 17.3 GHz with the suppression level better than −20 dB, and it has an acceptable sharp frequency response in the transition band. The measurement results are in good agreement with the simulation results

Increasing efficiency of two-phase flowmeters using frequency-domain feature extraction and neural network in the detector output spectrum

In this paper, three different regimes including annular, stratified and homogeneous in the range of 5%-90% void fraction, were simulated by Mont Carlo N-Particle (MCNP) Codes. In simulated structure, a cesium 137 source and two Nal detectors were used to record received photons. In this study, the Fast Fourier Transform (FFT) was applied to the registered signals from two detectors in order to analyze in the frequency domain. Several features of signals in the frequency domain were extracted using average value of fast Fourier transform, the amplitude of dominant frequency, kurtosis, Standard Deviation (STD), RMS (Root Mean Square) and Variance. The same features were extracted from analyzed signals of both detectors in order to find the best separation patterns. These extracted features were used as inputs of artificial neural networks (ANNs) to increase the efficiency of two-phase flowmeters. Two multi-layer perceptrons (MLP) neural networks were implemented in MATLAB software in order to classify flow regimes (annular, stratified and homogeneous) and predict the void fraction. All of the training and testing data were obtained correctly and the mean relative error percentage of the predicted void fraction was 1/15 %

Empirical data-driven multi-layer perceptron and radial basis function techniques in predicting the performance of nanofluid-based modified tubular solar collectors

In the present study, the modified evacuated tube solar collector (METSC) with a bypass pipe utilizing copper oxide/distilled water (Cu 2O/DW) nanofluid is experimented. Then, the performance of METSC was predicted through Artificial Neural Networks (ANNs) techniques. The input variables were different volumes of the storage tank from 5 to 8 l, various diameters of the bypass pipe from 6 to 10 mm, and various volumetric concentration of the nanofluid from 0 to 0.04. Also, the output variables were the temperature difference of fluid in 1-h period and the energetic efficiency of METSC. The results demonstrated that the METSC performance was mostly impacted by the tank volume alteration. Moreover, the optimum bypass tube diameter value was obtained, and it was denoted that using the Cu 2O/DW nanofluid enhances the daily energy efficiency of METSC up to 4%. Furthermore, it was shown that both MLP and RBF techniques are two reliable algorithms to predict the thermal characteristics of an METSC. The maximum amounts of mean relative percentage error for MLP and RBF algorithms were reported as 0.576 and 0.907, respectively. Hence, two mathematical models were reported for formulating the output variables in terms of the input variables using the MLP technique

A Novel Method for Ion Track Counting in Polycarbonate Detector

A computer program for recognizing and counting the track of ions that are detected with polycarbonate detector has been written using MATLAB software. There are different programs for counting the track of ions in different detectors. Algorithm of this program specially has been written for polycarbonate detector and also for low magnification of optical microscope. Thus, with this method as per image of optical microscope, greater numbers of ions are visible and general distribution of ions can be better known. However, the accuracy of counting program is very high