In this study, a new tri-band balanced band-pass filter (BPF) design based on a single-stepped-impedance ring resonator (SIRR) with four stepped stubs loaded on the feeding structure was proposed, analyzed, and design equations were derived. Using the SIRR properties in combination with open stepped stubs, multiple transmission zeros (TZs) were generated, and by adjusting the location of the TZs, high selectivity and an ultra-wide differential-mode (DM) stopband bandwidth were achieved. A pair of stepped stubs on the symmetry line of the filter was also integrated to enhance the common-mode (CM) rejection. Compared to other state-of-the-art differential multiband BPFs, superior performance in harmonic suppression and CM rejection was achieved while maintaining high selectivity and a simple planar design. A prototype tri-band balanced BPF with center frequencies of 1.7, 2.7, and 4.5 GHz was designed and fabricated. Results showed an ultra-wide DM upper stopband bandwidth of 11.1f(1) (up to 18.9 GHz) and a wideband CM suppression of S-CC21< -20 dB from 1.3 GHz to 5.9 GHz.

This paper presents a compact topology for implementing multiband bandpass filters. The design uses interconnected multimode resonators (MMRs) and multi-level impedance structures to achieve a specific frequency response. This approach simplifies the design of quadruple bandpass filters for 4G and 5G applications. Since line widths cannot be adjusted post-construction, Aresonance positions require tuning. To evaluate the filter design process, a prototype incorporating MMRs was designed, manufactured, and analyzed, demonstrating close alignment between analytical predictions and experimental measurements, despite no simulation or optimization being performed during the design phase, except for the result of verification. AAdditionally, a design criterion is established to facilitate the rapid and reliable synthesis of multiband responses by varying only a few geometrical parameters of the MMRs. A simulation of this structure was conducted using CST software to confirm the proposed theory's accuracy. A reverse-biased varactor diode, which functions as a capacitor with specific admittance, is utilized to provide the necessary tuning capability. The paper also highlights the impact of the varactor diode's admittance on resonance location adjustments. To validate the design, the authors present a fabricated prototype of the proposed filter, which features quarter bands at 1.8, 2.1, 2.7, and 3.4 GHz, achieving an attenuations greater thanA-15 dB. AThe quarter band filter is primarily used in wireless telecommunications networks. Due to their specialized design, these filters can process multiple frequency bands simultaneously, enhancing communication quality and increasing network capacity in crowded and interference-prone environments.

This article proposes a Quasi-Z-source converter that utilizes a three-level circuit in the output section to enhance voltage gain and level the output voltage. Compared to similar structures, this design employs only one switch, resulting in a straightforward and linear converter performance. Additionally, the converter control is implemented in PWM (Pulse Width Modulation). Due to the simple circuit structure and the creation of soft-switching conditions for the switching elements, conduction, switching, and ohmic losses in this converter have been reduced. Consequently, the efficiency of this converter and its EMI effects have improved compared to similar structures. Furthermore, this converter features a common ground between the input and output, which contributes to noise reduction. On the other hand, due to reduced voltage and current stresses on the active components, this converter can be used for applications with both full and half output voltages, especially at higher power levels. Theoretical, circuit, small-signal analyses, and design considerations for the converter are presented in the article. An experimental prototype of the proposed converter has been implemented at 200 watts for an input voltage of 36 volts and an output voltage of 720 volts. The converter has an efficiency of 97.6%. The results obtained from the converter’s implementation are compared with theoretical results, confirming the converter’s performance.

This paper introduces a new design for an interdigital capacitor (IDC) resonator, which results in a modified and improved version of the traditional IDC resonator. By employing fingers (parallel conductive strips) of varying widths in the design, enhanced control over the resonant frequencies is attained. This approach also mitigates undesirable parasitic effects in the IDC that can lead to improved harmonic suppression and common-mode (CM) rejection. For demonstration, a dual-band balanced bandpass filter (B-BPF) with passbands centred at 3.1 GHz and 5.1 GHz is designed and fabricated. Differential-mode (DM) stopband bandwidth of under 15 dB up to 18.9 GHz or 6.1f1 and CM rejection of under 20 dB from 0 to 17.3 GHz is achieved. The measured results for this filter, when compared against the simulation outputs, exhibit a satisfactory level of alignment and corroboration. This innovative filter can contribute to advancing wireless communication technologies, particularly in WiMAX and Wi-Fi 6E systems.

Memristive devices include memristor, memcapacitor, and meminductor. Due to the adjustable resistance of the memristor, adjustable capacity of memcapacitor and adjustable inductance of meminductor, these devices can be used in the design of many analog circuits, including sinusoidal oscillators. Designing and implementation of a low-frequency voltage-controlled oscillator to achieve a wide tuning range, while meeting practical constraints such as small area and low power consumption, is a challenge. This challenge is overcome by replacing the resistors that occupy a large Silicon area in the conventional design with memristors, and hence smaller values of capacitances are used. Therefore, this chapter proposes and characterizes an overview of the implementation of memristive-based oscillators that are used in Electrical Neural Stimulation. In this chapter, an overview of the use of memristive devices in the design of sinusoidal oscillators and voltage-controlled oscillators is presented.

The stepped-impedance combline band pass filter (BPF) with novel input and output networks based on a new proposed J-inverter, which increases the center frequency tuning range with constant bandwidth (BW), is discussed. The even and odd mode analysis shows that the stepped resonators provide the necessary conditions for the appropriate coupling coefficient to keep the BW constant. In order to create an appropriate quality factor, the new proposed J-inverter is used. In the frequency response of the stopband region, three transition zeros (TZs) are generated, which two of TZs are controllable. The proposed tunable BPF has been fabricated on RO4003 substrate with a dielectric constant of 3.38 and 0.813 mm thickness. The size of the filter is compact and is only 0.31 lambda gx0.1 lambda g$$ 0.31{\lambda}_{\mathrm{g}}\times 0.1{\lambda}_{\mathrm{g}} $$, where lambda g$$ {\lambda}_{\mathrm{g}} $$ is the guided wavelength at the lower center frequency. The center frequency is equal to 1.723 GHz and a frequency tuning range from 1.2 GHz to 2.246 GHz with 100 MHz constant 3 dB absolute BW, the insertion loss of 1.4-3.17 dB and return loss of 17.8-25.9 dB is achieved. Increasing the range of center frequency tunability of BPFs used to improve capabilities of communication systems. In this article with a combination of the stepped-impedance microstrip combline band pass filter and novel input/output networks based on a new proposed J-inverter, center frequency tunability was a significant increase. Also, in addition to obtaining excellent characteristics for the proposed tunable BPF, it is considered to provide a design method. image

This paper presents a modified model to calculate the fractal dimension of digital images. The estimation of fractal dimensions is crucial to fractal analysis and is popularly carried out through methods based on box counting. The problem with these approaches is that, most of them do not remove the potential effects of noise on fractal dimensions properly. Accordingly, this study examines the effects of three different type of noises on fractal dimensions by using different images taken from Background image database. The examination shows that the fractal dimensions change Significantly, after noise adding, so we put forward a noise-robust and efficient fractal dimension calculation method Which is a combination of two methods, the gray-level co-matrix algorithm and improved box counting method. The results of experiments on the Background image dataset confirm the robustness and efficiency of the proposed method.

In this article, we propose a tunable terahertz (THz) filter composed of graphene layers and a PVC substrate. A novel approach utilizing a static magnetic field is introduced to tune the resonance frequency. The presence of a magnetic field and gyromagnetic materials like graphene enables the proposed configuration to exhibit both TE and TM polarizations in the output structure. Additionally, a remarkable tunability of about 5 THz bandwidth is achieved, a considerably high value compared to existing works. All results are obtained through numerical simulations using MATLAB software based on the transfer matrix method (TMM), and the accuracy is verified using COMSOL software. With nearly zero transmission, this exceptionally tunable THz filter holds great potential for various applications, including THz spectrometry.

This article proposes two new wideband common -mode noise suppression filters based on a defected ground structure. The first design uses the Butterworth equivalent circuit achieving a fractional bandwidth of 117 %. At first, the resonators are arranged next to each other and the equivalent circuit is extracted. Also, samples with different dimensions of resonators are prepared by electromagnetic simulation analysis, and the fuzzy interpolation method is used for estimating the circuit behavior. The ADS software is used to optimize the values of the variables to achieve the desired bandwidth in the schematic environment. This paper utilizes the Taguchi method to strike a balance between various parameters in the filter design, aiming to minimize errors during the fabrication process. Then, the new values estimated with the fuzzy interpolation method are verified by electromagnetic simulation. The fractional bandwidth of the filter increases to 124 %, and noise can be suppressed by more than 10 dB at the center frequency of 21.45 GHz in the range from 8.1 to 34.8 GHz, with a loss of less than 3 dB in the differential lines. A new equivalent circuit is proposed using the first -order Chebyshev model. It is observed that the electromagnetic simulations and circuit modeling have good agreement with the measurements. Moreover, the eye pattern with a speed rate of 21.45 Gb/s is proposed for USB 3.2 and HDMI 2.0 applications.

The design of balanced filters based on composite right/left hand (CRLH) structure is well developed. Among those, few designs exist which although they provide some good responses, suffer from narrow stopbands and interdependent passbands. This paper proposes a new technique for improving the characteristics of dual-band balanced bandpass filters (B-BPFs) based on planar CRLH. Using unequal inductive stubs (UISs) attached to the interdigital capacitor (IDC) unit cell, we were able to achieve outstanding harmonic suppression and passband controllability. This structure offers higher degrees of freedom compared to conventional designs and provides better control over the filter specifications. Mathematical modeling, analysis, simulation, fabrication, and performance measurement of the proposed technique in a dual-band B-BPF are also provided. Our work resulted in an independent and controllable dual-band B-BPF with ultra-wide upper differential-mode (DM) stopband of 5.9 f 1 and common-mode (CM) suppression of 40.4 and 32.6 dB for the first and second bands, respectively.

Convolutional neural networks (CNNs) are the most important branch of deep learning (DL) and have experienced rapid development in recent years. A major challenge in using these networks is their large number of parameters, which result in high computational and time costs in real-world applications. In many cases, this increase in costs is due to the design of deeper networks with more parameters for achieving higher accuracy. The present paper employed evolutionary algorithms (EAs) to introduce a method that can identify the best weights and use them to construct more accurate CNNs, hence eliminating the need for deeper networks. At the end of the article, the CNN obtained from the proposed algorithm is compared with the best existing CNNs; which shows that the proposed CNN has increased the classification accuracy, while the number of its parameters is much less, and as a result, it saves computing resources and time.

Multistage amplifiers have become appropriate choices for high-speed electronics and data conversion. Because of the large number of high-impedance nodes, frequency compensation has become the biggest challenge in the design of multistage amplifiers. The new compensation technique in this study uses two differential stages to organize feedforward and feedback paths. Five Miller loops and a 500-pF load capacitor are driven by just two tiny compensating capacitors, each with a capacitance of less than 10 pF. The symbolic transfer function is calculated to estimate the circuit dynamics and HSPICE and TSMC 0.18 mu m. CMOS technology is used to simulate the proposed five-stage amplifier. A straightforward iterative approach is also used to optimize the circuit parameters given a known cost function. According to simulation and mathematical results, the proposed structure has a DC gain of 190 dB, a gain bandwidth product of 15 MHz, a phase margin of 89 degrees, and a power dissipation of 590 mu W.

The present paper proposes a passive miniature triplexer for highly isolated three-port with bandpass filter structures based on microstrip technology for ultra-wideband. The proposed structure is applied with three output ports operating at three frequency bands (5.00 - 5.600 GHz) with an efficiency of 72.1% and 500 MHz bandwidth, (16.60 -17.90 GHz) with an efficiency of 69% and 1.3 GHz bandwidth, and (42.0 -48.50 GHz), with an efficiency of 63% and 6.5 GHz bandwidth, which are suitable for 5G Ultra-Wideband receivers. To reduce the dimensions of the proposed triplexer, the Geometry Resonator Network (GRN), Electro-Magnetic Coupling (EMC), Direct-Coupled Resonator (DCR), Branch Connection Filter (BCF), Stepped-Impedance Resonator (SIR), and Planar/non-Planar Transmission Line (P-nPTL) techniques are used. The proposed design can be widely used in uplink/downlink, enhanced Mobile Broad-Band (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), Mobile Roaming Revisited (MRR), and Reconfigurable Multi Technology Core (RMTC) applications, which is very important in signal transmission. The proposed triplexer, which has a miniature size of 0.2λ×0.2λ, is simulated in the Keysight Advanced Designed System (ADS) software. The small size of the proposed triplexer makes it a suitable option for many applications in which the physical dimensions are a design challenge.

The synchronization of chaotic memristive systems with sinusoidal oscillators in order to achieve fully sinusoidal response can be included among the most important ongoing research topics in nonlinear sciences. In this paper, the purpose of controlling the chaotic oscillator based on memristive devices is to achieve sinusoidal response by synchronizing its response with the response of sinusoidal colpitts oscillator. For this purpose, sinusoidal synchronizations between two distinct dynamical systems with different order are investigated. Accordingly, we provided a sufficient condition in order to control the chaos in the memristive oscillator based on memcapacitor and meminductor, in order to achieve fully sinusoidal response with constant amplitude. For this purpose, an adaptive feedback controller is designed to synchronize the states of the master and slave oscillators. Numerical simulations are performed to verify the effectiveness of the proposed control scheme.

The improved three-dimensional imaging system by near-infrared light emission in breast tissue to more accurate diagnosis of tumour is presented in this paper. Based on the repeated experiments in this research, the result is that in this imaging system a more accurate diagnosis of abnormal area depends on the location of the sources and detectors. Therefore, an optimal location model has been proposed to a more suitable placement of sources and detectors. In this article, human samples with the breast cancer have not been examined due to the inaccessibility of three-dimensional imaging system by near-infrared lights. These experiments should have been conducted frequently for obtaining the more accurate reconstructed images, in order to evaluate the optical image reconstruction toolbox of NIRFAST 7.2 that has been coded in MATLAB programming environment and then the obtained results have been compared with the results of similar articles. The obtained results have shown that the proposed placement of sources and detectors has detected the abnormal area with a much lower error rate as well as the proposed placement of sources and detectors has provided a good result in simultaneous diagnosis of the two abnormal areas.

Graphene transistors are promising candidates for nano-circuits in telecommunication bands due to their high amplification bandwidth, extremely high carrier mobility, high saturation velocity, and the good electric conductance of the graphene channel. In this study, the parameters of a compact model are implemented in the Verilog-A language. An out-phasing power amplifier is designed using microstrip input/output matching, bias network, and quarter-wave Chireix divider/combiner over the frequency range of 2–4 GHz. The simulation results of graphene out-phasing power amplifier in advanced design system software show an increase of about 14 dB in the output gain, an intermodulation distortion (IMD) suppression of better than − 21.8 dBc, and a DC power consumption of 20 mW. In addition, the figures of merit of the proposed design show improvements in terms of gain, IMD, power consumption, and input/output return loss compared to other graphene amplifiers at different frequencies. A comparison of our design with some other amplifiers in various technologies at different frequencies shows a good gain and better IMD suppression in our design. Moreover, the power consumption, input/output return loss, and bandwidth of our strategy are relatively improved.

This work presents an object recognition algorithm that combines local binary pattern (LBP) based on fuzzy logic approach and active contour model for segmenting different images to detect textured objects. Initially, images containing objects are segmented using the fuzzy logic-optimized LBP method. Then, we eliminate the image noise. Finally, utilizing a Chan-Vese active contour method, the target object of the image is highlighted. The segmentation has been compared with the classical LBP technique and the results indicated higher accuracy and quality for highlighting the object from the background. The classification of highlighted objects is performed with a convolution neural network (CNN). To authenticate the proposed approach, 140 images with the classification of 10 different objects were used. The simulation depicted that the proposed method has better results than other methods both in terms of segmentation error and performance. Significantly, CNN classification also showed a classification accuracy of 92.8%.

The present paper proposes a six-FinFET two-memcapacitor (6T2MC) non-volatile static random-access memory (NVSRAM). In this design, the two memcapacitors are used as non-volatile memory elements. The proposed cell is flexible against data loss when turned off and offers significant improvement in read and write operations compared to previous NVSRAMs. The performance of the new NVSRAM design is evaluated in terms of read and write operation at particular nanometric feature sizes. Moreover, the proposed 6T2MC cell is compared with 8T2R, 8T1R, 7T1R, and 7T2R cells. The results show that 6T2MC has a 5.50% lower write delay and 98.35% lower read delay compared to 7T2R and 7T1R cells, respectively. The 6T2MC cell exhibits 38.86% lower power consumption and 23.80% lower leakage power than 7T2R and 7T1R cells. The proposed cell is significantly improved in terms of HSNM, RSNM, and WSNM compared to 8T2R, 8T1R, 7T2R, and 7T1R cells, respectively. Important cell parameters, such as power consumption, data read/write delay, and SNM, are significantly improved. The superior characteristics of FinFET over MOSFET and the combination of this technology with memcapacitors lead to significant improvement in the proposed design.

Deep neural networks (DNNs) are promising alternatives to simulate physical problems. These networks are capable of eliminating the requirement of numerical iterations. The DNNs could learn the governing physics of engineering problems through a learning process. The structure of deep networks and parameters of the training process are two basic factors that influence the simulation accuracy of DNNs. The loss function is the main part of the training process that determines the goal of training. During the training process, lost function regularly is used to adapt parameters of the deep network. The subject of using DNNs to learn the physical images is a novel topic and demands novel loss functions to capture the physical meanings. Thus, for the first time, the present study aims to develop new loss functions to enhance the training process of DNNs. Here, three novel loss functions were introduced and examined to estimate the temperature distributions in thermal conduction problems. The images of temperature distribution obtained in the present research were systematically compared with the literature data. The results showed that one of the introduced loss functions could significantly outperformance the literature loss functions available in the literature. Using a new loss function improved the mean error by 67.1%. Moreover, using new loss functions eliminated the pixels predictions (with large errors) by 96%.