Search Results (73)

In this paper, a new algorithm for the training of Locally Recurrent Neural Networks (LRNNs) is presented, which aims to reduce computational complexity and at the same time guarantee the stability of the network during the training. The main feature of the proposed algorithm is the capability to represent the gradient of the error in an explicit form. The algorithm builds on the interpretation of Fibonacci’s sequence as the output of an IIR second-order filter, which makes it possible to use Binet’s formula that allows the generic terms of the sequence to be calculated directly. Thanks to this approach, the gradient of the loss function during the training can be explicitly calculated, and it can be expressed in terms of the parameters, which control the stability of the neural network. Full article

A new numerical method for solving Volterra non-linear convolution integral equations (NLCVIEs) of the second kind is presented in this work. This new approach, named IIRFM-A, is based on the combined use of the Laplace transformation, a first-order decomposition, a bilinear transformation, and the Adomian decomposition. Unlike most numerical methods based on the Laplace transformation, the IIRFM-A method has the dual advantage of requiring neither the calculation of the Laplace transform of the source function nor that of intermediate inverse Laplace transforms. The application of this new method to the case of non-convolutive multiplicative kernels is also introduced in this work. Several numerical examples are presented to illustrate the great flexibility and efficiency of this new approach. A concrete thermal problem, described by a non-linear convolutive Volterra integral equation, is also solved numerically using the new IIRFM-A method. In addition, this new approach extends for the first time the field of use of first-order recursive filters, usually restricted to the case of linear ordinary differential equations (ODEs) with constant coefficients, to the case of non-linear ODEs with variable coefficients. This extension represents a major step forward in the field of recursive filters. Full article

This paper presents a programmable digital filtering unit dedicated to operating with signals from infrared (IR) detection modules. The designed device is quite useful for increasing the signal-to-noise ratio due to the reduction in noise and interference from detector–amplifier circuits or external radiation sources. Moreover, the developed device is flexible due to the possibility of programming the desired filter types and their responses. In the circuit, an advanced field-programmable gate array FPGA chip was used to ensure an adequate number of resources that are necessary to implement an effective filtration process. The proposed circuity was assisted by a 32-bit microcontroller to perform controlling functions and could operate at frequency sampling of up to 40 MSa/s with 16-bit resolution. In addition, in our application, the sampling frequency decimation enabled obtaining relatively narrow passband characteristics also in the low frequency range. The filtered signal was available in real time at the digital-to-analog converter output. In the paper, we showed results of simulations and real measurements of filters implementation in the FPGA device. Moreover, we also presented a practical application of the proposed circuit in cooperation with an InAsSb mid-IR detector module, where its self-noise was effectively reduced. The presented device can be regarded as an attractive alternative to the lock-in technique, artificial intelligence algorithms, or wavelet transform in applications where their use is impossible or problematic. Comparing the presented device with the previous proposal, a higher signal-to-noise ratio improvement and wider bandwidth of operation were obtained. Full article

An infinite impulse response (IIR) system might comprise a multimodal error surface and accurately discovering the appropriate filter parameters for system modeling remains complicated. The swarm intelligence algorithms facilitate the IIR filter’s parameters by exploring parameter domains and exploiting acceptable filter sets. This paper presents an enhanced symmetric sand cat swarm optimization with multiple strategies (MSSCSO) to achieve adaptive IIR system identification. The principal objective is to recognize the most appropriate regulating coefficients and to minimize the mean square error (MSE) between an unidentified system’s input and the IIR filter’s output. The MSSCSO with symmetric cooperative swarms integrates the ranking-based mutation operator, elite opposition-based learning strategy, and simplex method to capture supplementary advantages, disrupt regional extreme solutions, and identify the finest potential solutions. The MSSCSO not only receives extensive exploration and exploitation to refrain from precocious convergence and foster computational efficiency; it also endures robustness and reliability to facilitate demographic variability and elevate estimation precision. The experimental results manifest that the practicality and feasibility of the MSSCSO are superior to those of other methods in terms of convergence speed, calculation precision, detection efficiency, regulating coefficients, and MSE fitness value. Full article

The objective of this paper is to first present some issues with impulse invariance filter (IIF) design during the design of digital infinite impulse response (IIR) filters. Engineers are often confused about some inconsistent observations. For instance, if the impulse response of a digital filter is designed using the impulse invariance procedure, then the analog and digital filters’ frequency and step responses are very different. Two simple remedies are presented in this paper. One is a post-processing approach that scales the frequency and step responses of the digital filter by the sampling interval T. Another one is a pre-processing approach that scales the impulse response of the analog filter by T. However, even after these remedies, there is still a steady state bias in the step response of the digital filter for certain cases where there is discontinuity in the analog impulse response. A recommendation is to include a correction term in the digital filter. After that, the steady state bias in the digital filter is then suppressed. Moreover, the MATLAB R2021a command “impinvar” needs to also include a correction term so that the frequency and step responses can be more accurate in the digital filter. Two comparative studies were carried out to compare the improved IIF filter with three competing digital IIR filter design methods. Although the above issues and improvements have been proposed by researchers in the past, many researchers, engineers, and students are still not aware of them. This paper provides a fresh revisit of these issues and improvements by using figures, equations, and examples. Proper credits are also given to those researchers who first pointed out those issues and improvements. It is hoped that through an open access journal, future rediscovery of issues and improvements in IIF can be prevented. Full article

Protoceratium reticulatum, a dinoflagellate species known for producing yessotoxins (YTX), can form harmful algal blooms (HABs) impacting marine life. This study examined how P. reticulatum influenced the physiological rates and affected the tissue health of juvenile scallops, Argopecten purpuratus. The scallops were exposed to non-toxic algae Isochrysis galbana (diet A) and mixtures where 30 and 70% of the non-toxic algae were replaced by the toxic algae P. reticulatum (diet B and C, respectively) for 15 days, followed by a 15-day recovery period (I. galbana). Results showed that the clearance rate (CR), inorganic ingestion rate (IIR), organic ingestion rate (OIR), and absorption rate (AR) were significantly reduced within the first seven days of exposure to toxic diets, with reductions of approximately 25% and 50% in diets B and C, respectively, compared to the non-toxic diet, and an increase in these parameters during the recovery stage. Histological observations revealed greater tissue damage in the digestive gland than in the gills, with a higher frequency of scallops with severe damage correlating with higher toxic diet content. Despite no direct impact on survival, the compromised physiological health of A. purpuratus juveniles suggests increased vulnerability to other stressors. These findings provide new insights into the filter-feeding behavior and selective filtration capabilities of scallops in the presence of toxic dinoflagellates and how scallops health can be compromised, contributing to the understanding of how HABs and associated toxins affect A. purpuratus. Full article

The goal of this study is to explore the effectiveness of applying multi-objective particle swarm optimization (MOPSO) algorithms in the design of infinite impulse response (IIR) filters. Given the widespread application of IIR filters in digital signal processing, the precision of their design plays a significant role in the system’s performance. Traditional design methods often encounter the problem of local optima, which limits further enhancement of the filter’s performance. This research proposes a method based on multi-objective particle swarm optimization algorithms, aiming not just to find the local optima but to identify the optimal global design parameters for the filters. The design methodology section will provide a detailed introduction to the application of multi-objective particle swarm optimization algorithms in the IIR filter design process, including particle initialization, velocity and position updates, and the definition of objective functions. Through multiple experiments using Butterworth and Chebyshev Type I filters as prototypes, as well as examining the differences in the performance among these filters in low-pass, high-pass, and band-pass configurations, this study compares their efficiencies. The minimum mean square error (MMSE) of this study reached 1.83, the mean error (ME) reached 2.34, and the standard deviation (SD) reached 0.03, which is better than the references. In summary, this research demonstrates that multi-objective particle swarm optimization algorithms are an effective and practical approach in the design of IIR filters. Full article

A new numerical method for solving Volterra linear convolution integral equations (CVIEs) of the second kind is presented in this work. This new approach uses first-order infinite impulse response digital filters method (IIRFM). Three convolutive kernels were analyzed, the unit kernel and two singular kernels: the logarithmic and generalized Abel kernels. The IIRFM is based on the combined use of the Laplace transformation, a first-order decomposition, and a bilinear transformation. This approach often leads to simple analytical expressions of the approximate solutions, enabling efficient numerical calculation, even using single-precision floating-point numbers. When compared with the method of homotopic perturbations with Laplace transformation (HPM-L), the IIRFM approach does not present, in linear cases, the convergence difficulties inherent to iterative approaches. Unlike most solution methods based on the Laplace transform, the IIRFM has the dual advantage of not requiring the calculation of the Laplace transform of the source function, and of not requiring the systematic calculation of inverse Laplace transforms. Full article

This paper focuses on the numerical study of spherical particle sedimentation, taking into account hydrodynamic interactions. Infinite impulse response (IIR) digital filters, specially tailored to solve the sedimentation dynamics, were used in the present study to numerically solve the coupled ordinary differential equations with the time-dependent coefficients of the problem. Hydrodynamic interactions are modeled using the Rotne–Prager–Yamakawa (RPY) approximation, to which a correction is made to better account for short-range interactions. In order to validate both the proposed numerical resolution method and the RPY correction, this paper begins with the study of two interacting spherical particle sedimentation methods. Comparisons with previously published analytical or numerical results confirm the relevance of the present approach. Full article

Sustainable transportation is crucial in addressing global road safety and environmental challenges. This study introduces a novel photonic radar system, leveraging Linear Frequency-Modulated Continuous Wave (LFMCW) technology for high-speed data transmission. Operating in a homodyne configuration, this system uses a single oscillator to generate both signal and reference waveforms. It incorporates mode division multiplexing (MDM) to enable the detection and ranging of multiple targets, even under adverse atmospheric conditions. To counter atmospheric attenuation, the system is equipped with a 2 × 2 MIMO technique and an Infinite Impulse Response (IIR) filter. Numerical simulations demonstrate the system’s superior performance in range resolution and target detection, achieving significant power improvements. The IIR filter further enhances detection, achieving a power improvement of 200% for target 1 and 276% for target 2. With low power requirements and enhancement through IIR filter equalization, this system presents a viable option for battery-operated vehicles. This innovative approach offers a low-power high-efficiency solution suitable for battery-operated vehicles, promoting safer and more reliable sustainable transportation. Full article

In this article, we describe a performance comparison conducted between several digital filters intended to mitigate the intrinsic noise observed in magnetometers. The considered filters were used to smooth the control signals derived from the magnetometers, which were present in an autonomous forestry machine. Three moving average FIR filters, based on rectangular Bartlett and Hanning windows, and an exponential moving average IIR filter were selected and analyzed. The trade-off between the noise reduction factor and the latency of the proposed filters was also investigated, taking into account the crucial importance of latency on real-time applications and control algorithms. Thus, a maximum latency value was used in the filter design procedure instead of the usual filter order. The experimental results and simulations show that the linear decay moving average (LDMA) and the raised cosine moving average (RCMA) filters outperformed the simple moving average (SMA) and the exponential moving average (EMA) in terms of noise reduction, for a fixed latency value, allowing a more accurate heading angle calculation and position control mechanism for autonomous and unmanned ground vehicles (UGVs). Full article

This paper focuses on both voltage transients and short-duration RMS variations, and presents a unique and heterogeneous approach to their assessment by applying AI tools. The database consists of both real (obtained from Lithuanian PQ monitoring campaigns) and synthetic data (obtained from the simulation and literature review). Firstly, this paper investigates the fundamental grid component and its harmonics filtering with an IIR shelving filter. Secondly, in a key part, both SVM and KNN are used to classify PQ events by their primary cause in the voltage–duration plane as well as by the type of short circuit in the three-dimensional voltage space. Thirdly, since it seemed to be difficult to interpret the results in the three-dimensional space, the new method, based on Clarke transformation, is developed to convert it to two-dimensional space. The method shows an outstanding performance by avoiding the loss of important information. In addition, a geometric analysis of the fault voltage in both two-dimensional and three-dimensional spaces revealed certain geometric patterns that are undoubtedly important for PQ classification. Finally, based on the results of a PQ monitoring campaign in the Lithuanian distribution grid, this paper presents a unique discussion regarding PQ assessment gaps that need to be solved in anticipation of a great leap forward and refers them to PQ legislation. Full article

One of the most common coal preparations is enrichment in a jig using a float regulation system. The latest solutions propose to compensate for significant measurement errors of the float by introducing a radiometric density meter operating on the principle of gamma radiation absorption into the bottom product discharge zone of the jig. The signal from the radiometric density meter detector is in the form of a sequence of pulses with a Poisson time distribution, which are counted by a counter, as a form of digital low-pass filter. The requirement to maintain accuracy at an appropriate level forces the measurement time to be extended, which worsens the dynamic properties. Changes in the density of the coal–water medium have an unsteady, cyclical course, resulting from the principle of operation of the jig. The research goal was to develop an algorithm for processing the signal from the radiation detector using an IIR filter in the measurement path in a way that ensures optimization of the dynamic properties of the radiometric density meter operating in the control system of the coal enrichment process in the jig. For this purpose, a low-pass IIR filter was introduced into the measurement path to process the signal from the pulse counter. The identified course of the medium density for one cycle (the first) served as a reference signal. A first-order IIR filter was proposed, with a constant parameter selected on the basis of the reference signal and a parameter depending on the time derivative of the identified density of the medium. The mean squared error MSE was adopted as an indicator for assessing the dynamic properties of the radiometric density meter. The results of simulation tests showed that introducing an IIR filter into the measurement path gives better results in terms of the adopted criterion than using a counter with a constant measurement time. The best results (MSE = 2.05 × 10⁻⁴) were obtained using an IIR filter with a parameter that is a linear function of the derivative of the medium density over time, determined for one air pulsation cycle and applied in four subsequent cycles. These results were obtained for an adaptive first-order filter with a variable parameter a from the designated range from 0.833 to 0.999, for a measurement time of 2 ms. Full article

To reduce computational load and memory consumption, multirate repetitive control (MRC) with downsampling rates provides a flexible and efficient design for proportional-integral multi-resonant repetitive control (PIMR-RC) systems for grid-tied inverters. However, in MRC systems, repetitive controllers with low sampling rates produce low delay periods, and integer-order phase lead compensation may cause undercompensation or overcompensation. These imprecise linear phase lead compensations may result in deteriorated control performance. To address these problems, based on an infinite impulse response (IIR) filter, a fractional-order phase lead proportional-integral multi-resonant multirate repetitive control (FPL-PIMR-MRC) is proposed for grid-tied inverters in this paper. The proposed method can provide a suitable fractional phase lead step to achieve a wide stability region, minor tracking errors, and low hardware costs. The IIR fractional-order lead filter design, stability analysis, and the step-by-step parameter tuning of the FPL-PIMR-MRC system are derived in detail. Finally, simulation performed confirms the feasibility and effectiveness of the proposed scheme. Full article

LoRa technology is being integrated into industrial applications as part of Industry 4.0 owing to its longer range and low power consumption. However, noise, interference, and the fading effect all have a negative impact on LoRa performance in an industrial environment, necessitating solutions to ensure reliable communication. This paper evaluates and compares LoRa’s performance in terms of packet error rate (PER) with and without forward error correction (FEC) in an industrial environment. The impact of integrating an infinite impulse response (IIR) or finite impulse response (FIR) filter into the LoRa architecture is also evaluated. Simulations are carried out in MATLAB at 868 MHz with a bandwidth of 125 kHz and two spreading factors of 7 and 12. Many-to-one and one-to-many communication modes are considered, as are line of sight (LOS) and non-line of Sight (NLOS) conditions. Simulation results show that, compared to an environment with additive white Gaussian noise (AWGN), LoRa technology suffers a significant degradation of its PER performance in industrial environments. Nevertheless, the use of forward error correction (FEC) contributes positively to offsetting this decline. Depending on the configuration and architecture examined, the gain in signal-to-noise ratio (SNR) using a 4/8 coding ratio ranges from 7 dB to 11 dB. Integrating IIR or FIR filters also boosts performance, with additional SNR gains ranging from 2 dB to 6 dB, depending on the simulation parameters. Full article