Analog Integrated Circuits and Signal Processing最新文献

The precision measurement of capacitance necessitates the utilisation of a precision capacitance bridge, wherein a sine signal serves as a reference. Consequently, the precision of the sine signal is of paramount importance for the precision measurement of capacitance. In the conventional method of generating a sine signal, a look-up table is employed as the data source. However, the look-up table approach necessitates an excessive amount of read-only memory space to fulfil the requirements of high-precision scenarios. In this paper, we proposes an novel algorithm based on Taylor expansion to calculate the sine function. This algorithm doesn’t use any read-only storage space. Compared with the Coordinate Rotation Digital Computer algorithm in computer, it is based on the pipelined architecture to balance latency and digital signal processor resource consumption. For the Lagrange residual term error problem of Taylor expansion, the optimization algorithm using trigonometric periodicity and the complementary algorithm of sine and cosine functions is proposed. To evaluate the accuracy of the sine function generated by the algorithm, direct digital synthesis and digital to analog converter outputs are utilized to improve the accuracy and enhance the total harmonic distortion as compared to the conventional algorithm.

In the present situation of health informatics, appropriate pre-processing tools are necessary to judge actual condition. In this direction, Electrocardiogram (ECG) is the right tool which shows electrical activity of the heart. This tool gives its output in the form of electrical signal having three different wave components namely; P-wave, QRS wave (complex), and T-wave. In this paper combination of three efficient techniques viz. Digital bandpass filtering (DBPF), Hilbert envelope, and Factor analysis is used for ECG signal analysis. The analysis of ECG signal is done by estimating position of R-peaks in MIT-BIH Arrhythmia (MIT-BIH Arr) database. The proposed technique has proved its utility in cardiology by establishing Sensitivity (Se) of 99.95%, Positive Predictivity (Pp) of 99.97%, Accuracy (Acc) of 99.92% and Signal-to-Noise Ratio (SNR) of 37.71dB in considered 18 datasets of MIT-BIH Arr database. In the common datasets used by different researchers, the proposed methodology secured Se of 99.98%, Pp of 99.98%, Acc of 99.96%, and SNR of 39.78dB. The proposed methodology is also compared with well established research works and showing significant improvements in their parameters viz. Se, Pp and Acc. Different work proposed by various authors on ECG signal analysis have been compared. The proposed technique is definitely important for medical engineering applications in estimating correct health condition (by R-peaks detection).

This manuscript presents a 4-element (40 × 40 mm²) and 8-element (80 × 80 mm²) Multiple-Input Multiple-Output (MIMO) antenna designed for 5th generation technology within the sub-6 GHz frequency range. Each element of the MIMO antenna, which comprises a perturbed pentagon rectangular-cut antenna, is arranged in an orthogonal configuration on a single substrate. To ensure optimal performance, a circular ring-like strip is added on the pentagon-shaped patch. The novel printed sub-6 GHz antenna is fed by a microstrip line. Parallel strips (4-element) and corner isolating strips on the ground plane (8-element) are the key segments that improve isolation. The unique MIMO antenna design contributes to the desired return loss and isolation characteristics. The achieved parameters for the designed antenna; Envelope Correlation Coefficient (ECC) < 0.002, Diversity Gain (DG) ≈9.99 dB and Channel Capacity Loss (CCL) < 0.1bps/ Hz, show acceptable MIMO performance. This design will support large-scale IoT utilization with better dependability and data throughput.

This paper introduces a novel fractional-order model of the classical RC electrical circuit by incorporating the generalized Caputo fractional derivative of order (0<psi le 1) and a fractional time constant (tau _{psi }). Using generalized Laplace and inverse Laplace transform techniques, explicit analytical solutions of the proposed model are derived. The study also conducts a comparative analysis between the new fractional RC circuit model and existing models based on classical integer-order derivatives, Caputo, Caputo–Fabrizio, and conformable fractional operators. The results demonstrate that the proposed model offers improved flexibility and accuracy in capturing the memory-dependent dynamics characteristic of real electrical systems. This work contributes to the growing field of fractional calculus applications in electrical engineering by providing a more comprehensive framework for modeling and analysis of RC circuits with non-integer order behavior.

The increasing complexity of modern energy systems, like electric vehicle charging and smart grids, necessitates efficient optimization techniques for power management. In modern energy systems, such as electric vehicle charging and smart grids, is their inability to accurately model the complex, non-linear relationships and dynamic conditions in modern energy systems. They may lack adaptability, leading to inefficiencies and suboptimal performance. This manuscript proposes a hybrid approach that depends on the Internet of Things (IoT) aided power monitoring system for smart-grid (SG). The proposed hybrid strategy is combined with Dwarf Mongoose Optimization (DMO) and Quantum Neural Network (QNN). Typically, it’s referred to as the DMO-QNN technique. The primary goal of the DMO-QNN approach is to improve the efficiency of IoT-based energy monitoring, which can monitor and evaluate electrical characteristics such as load power, voltage, current, and active power usage. The DMO technique ensures increased system efficacy, improves living quality, and streamlines processes in a range of sectors. The QNN predicts the optimal control signal for the sensor. The proposed strategy has improved the efficiency of electrical parameters, like voltage, current, load-power, and active-power consumption. According to the simulation research, the proposed approach outperforms the current approaches in terms of efficiency, with a 99% rate. Overall, the proposed system achieves peak efficiency, confirming its effectiveness for intelligent energy management in modern smart grid environments.

The main goal of the designed research is to find a powerful tool for adjusting and tuning polarization in microstrip patch antennas. That surely this practical platform, it is the same as graphene. In fact, the right- and left-hand circular polarization and linear polarization can be achieved by turning on and off the chemical potential in the cuts created on the diagonal edges of the antenna. In the structure of the antenna, a triangular and square scheme of gold has been worked. One of the important features of the presented structure is frequency reconfigurable. The graph model has been used in the analysis, design, and modelling of the reconfigurable graphene-based antenna. According to the requirements of the design, the central frequency of the antenna is set at 0.67 THz. Silicon dioxide is considered as the substrate of the design. In the range of 0.65 THz through 0.7 THz, the matching and polarization are suitable. S₁₁ is less than -14 dB for all types of polarization. Radiation efficiency is estimated at about 50%. Eventually, the outputs of return loss, S₁₁ sweep, axial ratio, radiation efficiency, 2D and 3D far-field radiation patterns, E-field distribution, and current density distribution have been reported.

This article introduces the synchronization of a specific category of hyperchaotic systems characterized by unknown variables such as uncertainty and disturbance. It achieves synchronization using an adaptive sliding mode controller, while notably utilizing a reduced number of control signals compared to the system's dimension. An early step in the first part of this investigation comprises the development of a sliding mode control scheme. This approach involves two control signals with the primary goal of synchronizing two Lorenz-Stenflo (LS) hyperchaotic systems. These systems are distinguished by well-defined parameters and the systems are sensitive to disturbance inputs as well as uncertainties. Further, in the pursuit of synchronizing two LS hyperchaotic systems marked by unknown parameters and influenced by disturbance inputs and uncertainties, two control signals come into play. Notably, in this context, the determination of these elusive parameters is facilitated through the employment of an adaptive rule, thereby enhancing the synchronization process. The effectiveness of the anticipated control mechanism is assessed by employing the Lyapunov stability approach, with a focus on determining its stability level. Synchronization and stability have been shown by numerical simulations. Analog circuit designs of the LS hyperchaotic system, along with the synchronization of the proposed pair using known system parameters through the Sliding Mode Control (SMC) approach, are implemented using NI Multisim software. The results from the NI Multisim circuit realization validate the outcomes of the matlab simulations.

A new third-order sinusoidal oscillator is presented, employing three voltage conveyors (VCIIs), three resistors, and three grounded capacitors—a configuration highly suitable for CMOS integrated circuit implementation. The circuit offers independent control of the condition of oscillation and frequency of oscillation via virtually grounded resistors, which can be realized using MOSFETs or FETs. Compared to previously reported CC-based third-order oscillators, the proposed design offers significant advantages, including the generation of two distinct quadrature voltage outputs at the buffered ports of the VCIIs. The proposed design has been validated, demonstrating a frequency error and total harmonic distortion (THD) within 4% across the entire operating range. The functionality of the circuit has been verified through both experimental validations using AD844-type CFOAs and SPICE simulations based on 0.18 µm CMOS process parameters.

As computing systems increasingly demand higher performance and lower power consumption, the need for energy-efficient and reliable arithmetic circuits has increased. Full adders, which are essential components of arithmetic units, play a critical role in optimizing power and performance in modern computing architectures. This paper presents a comparative analysis of a fault-tolerant multiplexer (MUX)-based Modified and Full Swing Full Adder (MFSFA), implemented in both CMOS 45 nm technology and Quantum-dot Cellular Automata (QCA) technology. We evaluate energy dissipation and power consumption using the Cadence 45 nm tool for CMOS and QCADesigner for QCA. Our findings show that while CMOS 45 nm technology provides strong performance, QCA designs achieve significant reductions in energy dissipation, making them suitable for ultra-low power applications. The trade-offs among power, area, and delay are examined, revealing the strengths and limitations of each technology. For the proposed CMOS 45 nm-based MFSFA, we note a delay of 118.75 ps, average power dissipation of 260 µW, and area of 131.76 μm² at 450 mV with an improvement of 65.19%, 60.5% and 51.03% those parameters respectively. In contrast, QCA technology shows parameters of 4 ps, 0.18 nW, and 0.05 μm² with an improvement of 91% and 82.14% in power dissipation and area respectively. This study highlights QCA’s potential as a viable alternative to traditional CMOS for energy-efficient, fault-tolerant circuit design in resource-constrained environments.

This paper presents a high-performance wireless architecture for fetal monitoring systems, integrating Space Time Block Coding (STBC), novel Double Throughput Multiple Accumulate (DTMAC), and early Fetal Electrocardiogram (FECG) prediction unit to address challenges in data reliability, security, and processing efficiency. STBC enhances communication robustness in fading environments by leveraging spatial and temporal diversity, while LMS-based adaptive beamforming improves signal reception and enables dynamic early prediction of FECG signals. A lightweight Naïve Bayes classifier is employed to classify fetal signals with high accuracy. For secure data transmission, a low-overhead AES encryption scheme using Linear Feedback Shift Registers (LFSRs) is implemented. The DTMAC unit, designed with a Ladner-Fisher based double-precision accumulate adder, significantly accelerates multiply-accumulate operations. The architecture was modeled in Verilog HDL and synthesized using Xilinx Vivado. Evaluation against existing methods demonstrates improved performance, with lookup table (LUT) usage reduced to 543, gate count minimized to 4,692, and memory usage decreased to 164,422 KB. Power consumption was lowered to 156.70 mW, with a 22.4% reduction in latency and an 18.6% increase in throughput. Validation was conducted using real-time FECG datasets from MIT PhysioNet. These results highlight the proposed system's efficiency in delivering secure, accurate, and real-time wireless fetal monitoring, making it a promising solution for next-generation healthcare applications.