Low Cross-correlation Research Articles

Ultra-short term wind power prediction method based on LightGBM and transformer

Abstract Accurate ultra-short-term wind power prediction is very important for the safe and stable operation of the power system. At present, most wind power forecasting systems use numerical weather forecast data and the data collected by the Supervisory Control And Data Acquisition (SCADA) system. However, these data have the characteristics of high data dimension, feature redundancy, and feature correlation. Therefore, in the process of ultra-short power prediction, it is necessary to select features with high power correlation and low cross-correlation between features. In this paper, a feature selection method for wind power prediction based on LightGBM is proposed to calculate the importance of all features and determine the preliminary selected features. Then, the maximum information coefficient is used to construct the correlation discriminant matrix, according to which the features with similar importance in a single screening are evaluated, and the input features with high similarity are discarded. In addition, in order to improve the accuracy of the system’s wind power prediction, this paper uses the effective features extracted by LightGBM to design an ultra-short-term power prediction method based on Transformer. The results show that the RMSE of ultra-short-term wind power prediction is 7.3%.

Perturbation Transmit Beamformer Based Fast Constant Modulus MIMO Radar Waveform Design

In this paper, a fast method to generate a constant-modulus (CM) waveform for a multiple-input, multiple-output, (MIMO) radar is proposed. To simplify the optimization process, the design of the transmit waveform is decoupled from the design of transmit beamformers (TBs) and subpulses. To further improve the computational efficiency, the TBs’ optimization is conducted in parallel, and a linear programming model is proposed to match the desired beampattern. Additionally, we incorporate the perturbation vectors into the TBs’ optimization so that the TBs can be adjusted to satisfy the CM constraint. To quickly generate the CM subpulses with the desired range-compression (RC) performance, the classical linear frequency modulation (LFM) signal and non-LFM (NLFM) are adopted as subpulses. Meanwhile, to guarantee the RC performance of the final angular waveform, the selection of LFM signal parameters is analyzed to achieve a low cross-correlation between subpulses. Numerical simulations verify the transmit beampattern performance, RC performance, and computational efficiency of the proposed method.

A Kinetic Model for Catalytic N-Butane Oxidative Dehydrogenation under Oxygen-Free Reaction Conditions in a Fluidized CREC Riser Simulator

This study considers the development of a kinetic model for the n-butane oxidative dehydrogenation (ODH) to C4-olefins using a VOx/MgO−γAl2O3 catalyst. The prepared catalyst contained 5 wt% V on an MgO modified γAl2O3 support. The developed catalyst exhibited both weak and medium acid sites, as revealed by NH3-temperature-programmed desorption. TPR/TPO analyses also indicated that 73% of the loaded VOx was reducible. Kinetic experiments were conducted in a fluidized CREC Riser Simulator at temperatures ranging from 475–550 °C and residence times of 5–20 s. An optimal C4-olefin selectivity of 86% was achieved at 500 °C and 10 s, with this selectivity then decreasing at higher temperatures and longer residence times. The kinetic model developed involved a Langmuir–Hinshelwood-type of kinetics that incorporated cracking, oxydehydrogenation, and complete oxidation reactions. Model parameters were determined by fitting experimental data with kinetic parameters established with narrow 95% confidence intervals and low cross-correlation.

Inverse Synthetic Aperture Radar Imaging of Space Targets Using Wideband Pseudo-Noise Signals with Low Peak-to-Average Power Ratio

With the number of new satellites increasing dramatically, comprehensive space surveillance is becoming increasingly important. Therefore, high-resolution inverse synthetic aperture radar (ISAR) imaging of satellites can provide an in-situ assessment of the satellites. This paper demonstrates that pseudo-noise signals can also be used for satellite imaging, in addition to classical linear frequency-modulated chirp signals. Pseudo-noise transmission signals offer the advantage of very low cross-correlation values. This, for instance, enables the possibility of a system with multiple channels transmitting instantaneously. Furthermore, it can significantly reduce signal interference with other systems operating in the same frequency spectrum, which is of particular interest for high-bandwidth, high-power systems such as satellite imaging radars. A new routine has been introduced to generate a wideband pseudo-noise signal with a peak-to-average power ratio (PAPR) similar to that of a chirp signal. This is essential for applications where the transmit signal power budget is sharply limited by the high-power amplifier. The paper presents both theoretical descriptions and analysis of the generated pseudo-noise signal as well as the results of an imaging measurement of a real space target using the introduced pseudo-noise signals.

Random broadband filters based on combination of metasurface and multilayer thin films for hyperspectral imaging

Metasurface based micro-spectrometer presents a promising avenue for achieving compact, lightweight, and cost-effective solutions for miniaturization of hyperspectral imaging systems. Nevertheless, this type of design encounter limitations primarily due to constrained manipulation mechanism of light field, resulting in high cross-correlation among transmission spectra and imperfect reconstructed images. In this paper, we propose and numerically demonstrate a micro-spectrometer based on metasurface combined with multilayer thin films, whose spectral response improves performance for application, i.e. achieving low spectral cross-correlation. Additionally, we incorporate particle swarm optimization with compressed sensing algorithm to optimize the proposed micro-spectrometer. This approach effectively reconstructs both narrowband and broadband hyperspectral signals with minimal error, achieving an impressive 2 nm spectral resolution. The simulation results of hyperspectral imaging demonstrated that the proposed methodology successfully reconstructs broadband hyperspectral images with an average spectral fidelity of 91.42%. This method holds significant potential for integrating into smartphones and other portable spectrometers, advancing the design of compact hyperspectral imaging systems.

Spatial-Vibration-Modulation-Assisted Blade Damage Localization for Industrial Quadrotor UAVs

The rapid development of unmanned aerial vehicle (UAV) market has triggered the demand for UAV structural health monitoring technology, and blade damage has received extensive attention as a common mechanical fault. In this study, the spatial vibration modulation method (SVMM) is proposed to assist in blade damage localization for an industrial quadrotor UAV. The key to SVMM is that, by arranging silicone-made ring-shaped vibrators with randomly selected structural parameters on the beams of the UAV, the frequency transfer functions of these beams with low cross-correlation are achieved. With SVMM, high-accuracy blade damage localization capability can be realized under single sensor strategies on the symmetrical UAV. The study considers the situations of one and two damage locations, and the recognition accuracies are both 97%, while those without SVMM are 90% and 86%, respectively. The results show that SVMM can effectively enhance the localization capability for blade damage. Due to the customized frequency transfer functions, the technique proposed in this study shows potential in the fields of UAVs or other mechanical equipment for structural health monitoring and damage assessment.

Radar Characteristics and Causal Analysis of Two Consecutive Tornado Events Associated with Heavy Precipitation during the Mei-Yu Season

This paper comprehensively analyzed two consecutive tornado events associated with heavy precipitation during the Mei-yu season (a period of continuous rainy weather that occurs in the middle and lower reaches of the Yangtze River in China from mid-June to mid-July each year) and detailed the formation and development process of the tornadoes using Doppler weather radar, wind profiler radar, ERA5 reanalysis data, ground automatic station data and other multi-source data. The results showed that: (1) Small-scale vortices were triggered and developed during the eastward movement of the low vortex, forming two tornadoes successively on the eastern section of the Mei-yu front. (2) The presence of a gap on the front side of the reflectivity factor profile indicated that strong incoming airflow entered the updraft. Mesocyclones were detected with decreasing heights and increasing shear strengths. The bottom height of the tornado vortex signature (TVS) dropped to 0.7 km, and the shear value increased to 55.4 × 10−3 s−1. Tornado debris signatures (TDSs) could be seen with a low cross-correlation coefficient (CC) value area of 0.85–0.9 in the mesocyclone. The difference between the lowest-level difference velocity (LLDV) and the maximum difference velocity (MXDV) reached the largest value when a tornado occurred. (3) The continuously enhanced low-level jet propagated downward to form a super-low-level jet, and the strong wind direction and wind speed convergence in the boundary layer created a warm, moist and unstable atmosphere in Suzhou. With the entrainment of dry air, the northwest dry jet and the southeast moist jet stimulated the formation of a miniature supercell. (4) The low-level vertical wind shear of 0–1 km increased significantly upon tornado occurrence, which was more conducive to the formation and intensification of horizontal vorticity tubes. Encountering updrafts and downdrafts, the vorticity tubes might have been stretched and intensified. The first lightning jumps appeared 15 min and 66 min earlier than the Kunshan Bacheng tornado and the Taicang Liuhe tornado. The Liuhe tornado occurred during the stage when the lightning frequency reached its peak and then fell back.

Use of Explainable AI Algorithm Revealing Longitudinal Changes in Practice Patterns and Toxicity Models

Dosimetric constraints evolve as clinicians implement practice changes, requiring modeling approaches to be dynamic. We applied a semi-automated explainable artificial intelligence (eAI) algorithm and dashboard visualizations to model dysphagia and xerostomia for head and neck cancer patients. We coupled a large, comprehensive, "real-world" database to the eAI for discovery of features with the strongest combined statistical and machine learning based evidence and to identify clinically actionable thresholds. Cohort included 758 patients treated 2017-2021 for HN cancer with conventional fractionation. Features included age, sex, diagnosis, staging, chemotherapy, smoking and alcohol status, BMI, weight loss, re-simulation, DVH curves, PTV and OAR volumes. Patients were scored for toxicity within 2 yrs of RT for dysphagia grade ≥ 3 and xerostomia grade ≥ 2. Bootstrap resampling of thresholds, ROC-AUC, PR-ROC, SN, SP, F1 and diagnostic odds ratio was used to statistically profile strength of evidence for candidate features. XGBoost models with 10-fold cross validation were repeated (n = 20) to identify mean and CIs for statistical measures of predictions. DVH metrics included standard template values and those with highest statistical evidence and low cross correlation with other features. Backward feature selection was used to identify the most relevant feature subset, where the least informative feature is iteratively removed from the model. This workflow was repeated by year and overall. Annual incidence of dysphagia averaged 0.13 ± 0.02 overall years. Xerostomia incidence decreased from 0.32 to 0.12 (2017-2021). Box-whisker plots by year showed consistent reductions in standard practice toxicity linked DVH metric values. Median dose to superior constrictors (PCM), contralateral parotid and contralateral submandibular gland (SMG) declined from 2017 to 2021 by 48 to 33 Gy, 17 to 10 Gy, and 28 to 22 Gy respectively. Statistics of XGBoost models of dysphagia for all years were ROC-AUC = 0.72 ± 0.05. Strongest overall years predictors were Oral Cavity (OC) D50%[Gy] < 32, inferior PCM Max [Gy] < 60, contralateral SMG D10%[Gy] < 53 and use of Paclitaxel. Xerostomia models were less predictive with ROC-AUC = 0.65 ± 0.05. Strongest predictors over each year were ipsilateral parotid D30%[Gy] < 35, contralateral SMG D96%[Gy] < 18.4, and overall staging < II. Predictive features varied substantially by year for both, showing the most consistency for SMG doses. For example, OC D50%[Gy] < 27 and contralateral SMG D96%[Gy] < 18 dominated xerostomia model in 2017 but not in 2021 when practice norms shifted to lower doses. As OAR doses were systematically reduced, statistical and AI models evidence highlighted contralateral SMG dose as important to both dysphagia and xerostomia for clinical practice change. The "real-world" database + eAI + visualization dashboards provided a method for continuous learning as clinical practice changes.

Efficient binary sequence set designs for MIMO PMCW radar

Multiple-input multiple-output (MIMO) phase-modulated continuous wave (PMCW) radar systems have major advantages for mutual-interference mitigation over their linear frequency-modulated continuous wave (LFMCW) counterparts. To attain a virtual array length of M×M̃ with M transmit and M̃ receive antennas, a probing sequence set with both low auto-correlation sidelobes and low cross-correlations is needed for MIMO PMCW radar. To reduce the hardware cost of sequence generation, binary probing sequence (BPS) sets are desirable. We present herein four efficient computational algorithms to generate BPS sets with desirable properties, and arbitrary sequence lengths and arbitrary number of sequences in the set are allowed. When initialized by random BPS sets, they can be used to obtain many different BPS sets with similar properties, i.e., with large diversity. Moreover, fast Fourier transform (FFT) are exploited, making the algorithms computationally efficient. They can be used to design long BPS sets that are hardly possible using existing methods in the literature. The convergence properties and the relationships among the proposed algorithms are also analyzed under a unified framework. Numerical examples are included to illustrate the effectiveness of our designs.

Method for calculating the integrated biological age of a human

Abstract. Integral biological age (BA) encompasses a holistic assessment of an individual's overall physiological state, taking into account various biological markers that may contribute to the ageing process. This article presents a novel method for determining the integral biological age, a comprehensive measure that considers multiple biological markers and factors to assess an individual's ageing process. We will delve into the various components and biomarkers utilized in our method, including cardiorespiratory and musculoskeletal systems functionality, and other molecular markers associated with ageing. By combining these diverse indicators, we create an integrated framework that provides a holistic view of an individual's ageing trajectory. The study included 124 practically healthy people aged from 20 to 90 years, who were examined at the «D.F. Chebotarev Institute of Gerontology of the National Academy of Medical Sciences of Ukraine». People with pathologies of the cardiovascular, respiratory, endocrine and central nervous systems, chronic liver and kidney diseases, and pathologies of the hematopoietic system were excluded from the analysis. We recorded 74 indicators characterizing different body systems: hearing, cardiovascular, respiratory, and musculoskeletal systems, as well as autonomic regulation and metabolism. To build a model of integral BA, indicators of each of the systems that have the highest correlation with age were selected. An important selection criterion was the low cross-correlation of these indicators. The use of step-by-step multiple regression made it possible to select the most informative indicators and obtain an equation that relates the age of the subjects with a number of indicators of the main body systems. The resulting calculation formula includes 11 indicators characterizing different body systems. The coefficient of determination of the model R2 was 0.738, indicating the high accuracy of the created model. The mean absolute error of age calculation was 5.34±3.99 years. After correcting the systematic error of the regression equation, the average absolute error in calculating the age was 4.72±3.25 years. The rate of ageing was estimated as the difference between BA and CA. If this difference exceeds the value of the model error, a conclusion can be made about accelerated ageing. Thus, the method for assessing the rate of ageing developed by us has high accuracy and can be used to assess the risk of developing age-dependent pathology. The implementation of the proposed method will allow not only to identify people with the risk of developing pathology but also to assess the effectiveness of treatment, prophylactic and rehabilitation measures. Keywords: integral biological age; method calculation; cardiovascular; respiratory; musculoskeletal systems; metabolism; human

Bio-inspired camouflage communication in air imitating birds songs

Radio communication is the most common means of communication nowadays, however, radio interference technology is becoming mature. Once radio communications are disrupted in the forest, people would be left in a passive position without any effective communication method. Sound is an also effective carrier of information. To realize effective communication in the forest environment, we proposed a bio-inspired camouflage communication strategy(BCCS) by imitating bird songs and took the Verditer Flycatcher as an example to demonstrate the feasibility of BCCS. We proposed a compound characteristics grouping coding method based on the tree structure to divide syllables into 32 feature groups. And five time–frequency(T-F) characteristics of syllables were extracted as grouping layers: syllable length, average frequency, frequency trend, the standard deviation of global frequency, and the difference of local frequency standard deviations. Then the correlation was used as the unique identification of a syllable within the group. Syllables in the feature group were screened to ensure high autocorrelation and low cross-correlation, which are the key basis in decoding. Each individual syllable can encode 8 bits of binary information through compound characteristics coding and correlation coding. Since the communication sequence is completely composed of the original bird songs and follows the regularities of distribution, BCCS has a good camouflage ability. Experiments were carried out to verify the feasibility and camouflage ability of BCCS in the forest environment.

Low-disturbance automatic bias point control for optical IQ modulator using digital chaotic waveform as dither signals.

A low-disturbance automatic bias point control (ABC) method for optical in-phase and quadrature modulators (IQM) is proposed using digital chaotic waveform as dither signals. Two distinct chaotic signals, each with unique initial values, are introduced to the direct current (DC) port of IQM in conjunction with a DC voltage. Due to the robust autocorrelation performance and exceptionally low cross-correlation of chaotic signals, the proposed scheme is capable of mitigating the impact of low-frequency interference, signal-signal beat interference, and high-power RF-induced noise on transmitted signals. In addition, due to the broadwidth of chaotic signals, their power is distributed across a broad frequency range, resulting in a significant reduction in power spectral density (PSD). Compared to the conventional single-tone dither-based ABC method, the proposed scheme exhibits a reduction in peak power of the output chaotic signal by over 24.1 dB, thereby minimizing disturbance to the transmitted signal while maintaining superior accuracy and stability for ABC. The performance of ABC methods, based on single-tone and chaotic signal dithering, are experimentally evaluated in both 40Gbaud 16QAM and 20Gbaud 64QAM transmission systems. The results indicate that the utilization of chaotic dither signals leads to a reduction in measured bit error rate (BER) for 40Gbaud 16QAM and 20Gbaud 64QAM signals, with respective decreases from 2.48% to 1.26% and from 5.31% to 3.35% when the received optical power is -27dBm.

Measurements and Modeling of Large-Scale Channel Characteristics in Subway Tunnels at 1.8 and 5.8 GHz

Radio propagation characteristics in subway tunnels are significant for designing reliable wireless communications. To obtain large-scale channel characteristics, extensive propagation measurements are conducted in a straight subway tunnel at 1.8 and 5.8 GHz, respectively. Based on the measurements, some typical large-scale channel parameters are extracted and modeled, such as path loss, shadow fading, and channel correlation. The path loss exponents are found to be 2.83 and 2.55 at 1.8 and 5.8 GHz, respectively, with shadow fading standard deviation of 1.58 and 2.58 dB. Shadow fading decorrelation distance is 8.71 m for 1.8 GHz and 11.65 m for 5.8 GHz, respectively. Moreover, cross-correlation coefficient of shadow fading in two dual-link scenarios is around 0.1, which shows that there is fairly low cross-correlation in a subway tunnel. The results in this letter are useful for link budget, handover scheme design, and network planning of subway communication system.

New Spectrally Constrained Sequence Sets With Optimal Periodic Cross-Correlation

Spectrally constrained sequences (SCSs) play an important role in modern communication and radar systems operating over non-contiguous spectrum. Despite numerous research attempts over the past years, very few works are known on the constructions of optimal SCSs with low cross-correlations. In this paper, we address such a major problem by introducing a unifying framework to construct unimodular SCS families using circular Florentine rectangles (CFRs) and interleaving techniques. By leveraging the uniform power allocation in the frequency domain for all the admissible carriers (a necessary condition for beating the existing periodic correlation lower bound of SCSs), we present a tighter correlation lower bound and show that it is achievable by our proposed SCS families including multiple SCS sets with zero correlation zone properties.

An Unambiguity and Anti-Range Eclipse Method for PD Radar Using Biphase Coded Signals

Target detection is an important research content in the radar field. At present, efforts are being made to optimize the precision of detection information. In this paper, we use the high pulse repetition frequency (HPRF) transmission method and orthogonal biphase coded signals in each pulse to avoid velocity ambiguity and range ambiguity of radar detection. In addition, We also apply Walsh matrix and genetic algorithm (GA) to generate satisfying orthogonal biphase coded signals with low auto-correlation sidelobe peak and cross-correlation peak, which make the results more accurate. In a radar receiver, data rearrangement of echo signals is performed, and then pulse compression and moving target detection (MTD) are utilized to get the final velocity and range information of a target without velocity ambiguity and range ambiguity. Besides, a small transmitting pulse time width is adopted to reduce the working blind area, and two different high pulse repetition frequencies (HPRFs) are adopted to solve the problem of range eclipse. Simulation results finally prove the effectiveness and feasibility of the proposed method.

Patient-specific respiratory motion management using lung tumors vs fiducial markers for real-time tumor-tracking stereotactic body radiotherapy.

In real-time lung tumor-tracking stereotactic body radiotherapy (SBRT), tracking accuracy is related to radiotherapy efficacy. This study aimed to evaluate the respiratory movement relationship between a lung tumor and a fiducial marker position in each direction using four-dimensional (4D) computed tomography (CT) images. A series of 31 patients with a fiducial marker for lung SBRT was retrospectively analyzed using 4DCT. In the upper (UG) and middle and lower lobe groups (MLG), the cross-correlation coefficients of respiratory movement between the lung tumor and fiducial marker position in four directions (anterior-posterior, left-right, superior-inferior [SI], and three-dimensional [3D]) were calculated for each gating window (≤1, ≤2, and≤3mm). Subsequently, the proportions of phase numbers in unplanned irradiation (with lung tumors outside the gating window and fiducial markers inside the gating window) were calculated for each gating window. In the SI and 3D directions, the cross-correlation coefficients were significantly different between UG (mean r=0.59, 0.63, respectively) and MLG (mean r=0.95, 0.97, respectively). In both the groups, the proportions of phase numbers in unplanned irradiation were 11%, 28%, and 63% for the≤1-, ≤2-, and≤3-mm gating windows, respectively. Compared with MLG, fiducial markers for UG have low cross-correlation coefficients between the lung tumor and the fiducial marker position. Using 4DCT to assess the risk of unplanned irradiation in a gating window setting and selecting a high cross-correlation coefficient fiducial marker in advance are important for accurate treatment using lung SBRT.

UNJUK KERJA KODE ORTHOGONAL M-SEQUENCE DALAM SISTEM DIRECT SEQUENCE SPREAD SPECTRUM MELALUI KANAL MULTIPATH FA

Multipath and multi-user interference are the main challenges in wireless communication systems. This has become a driving force for the development of data transmission technology that is focused to overcome these problems, one of which is spread spectrum. Spread spectrum is applied to CDMA technology which has the limitations of MAI, so a spreading code is required with specifications that have a very low cross-correlation value as in the orthogonal m-sequence code. In this study, simulate the orthogonal m-sequence code with a length of 8 chips on a multipath fading channel using the Direct Sequence Spread Spectrum system with aims of assessing the performance of the orthogonal m-sequence code on a multipath fading channel, based on the effect of changes in the number of multipath components. The research method used is a Monte Carlo simulation on simulink with the output data in the form of a graph of the comparison value of BER with Eb/No. The results show that on the flat fading channel with the number of components multipath 1, the BER value of the simulation results is in accordance with the BER theory so that the simulation is valid and can be applied to frequency selective fading channels. In the frequency selective fading channel with the number of multipath components 4,6, and 8, the best performance was shown in the multipath 4 component with the smallest BER value, this was influenced by the ACF and CCF values so that the multipath 4 component had the lowest ISI and interference between users.

Auroral Oval Boundary Dynamics on the Nature of Geomagnetic Storm

During emergency events, we could significantly depend on the stable operation of radio communication, navigation, and radars. The ionosphere, especially its auroral regions, significantly influences radio systems, which is why scientists and engineers create systems to monitor these regions. Using data from the global GNSS network, we analyzed the 10 strongest magnetic storms of solar cycle 24: five coronal mass ejection-driven (CME-driven) and five high-speed stream-driven (HSS-driven) storms. The analysis was based on the calculation of the standard deviation of the total electron content (TEC) derivative (rate of TEC index, ROTI). Under all the storms, the ROTI featured similar dynamics: the average ROTI reaches the highest values during the main phase, and the higher the intensity is, the more intense and equatorward the average ROTI registered. The highest cross-correlations are observed with a lag of 1 h, between the IMF z-component Bz and the magnetic latitude where the highest ROTI values appear. The auroral electrojet (SME index) shows the highest impact on the ROTI dynamics. An increase in the space weather indices (in absolute value) is accompanied by a decrease in the latitude where the maximal ROTI occurs. We found that the peculiarities of a storm affect the ROTI dynamics: all the CME-driven storms feature a high cross-correlation (&gt;0.75) between the IMF z-component Bz and the magnetic latitude where the highest ROTI appears, while the HSS-driven storms feature a lower cross-correlation (&lt;0.75) between them. The difference in duration of similar (by maximal values of geomagnetic indices) HSS- and CME-driven storms could produce differences in the highest ROTI values. Correlations show that compared to HSS-driven storms, CME-driven ones more directly impact the ROTI values and locations of regions with a high ROTI.

Mathematical Analysis of the Peak Sidelobe Level of the Ambiguity Function for Random Phase Codes

By using uniformly distributed phases for each bit, one can generate a waveform with an almost ideal aperiodic ambiguity function (thumbtack). Moreover,a set of such codes will potentially exhibit low cross-correlation, making them a family of codes suitable for multiple and diverse applications, ranging from 1) MIMO radars, 2) addressing the joint radar-communication problems, 3) mitigating the interference issues of coexistence of multiple radar systems operating in the same region, and 4) increasing the robustness of the system to jamming. This article presents the full analysis of the probability density function of the peak sidelobe level of such codes, as well as a full treatment of the ambiguity function to show mathematically what could be obtained by generating random phase codes. A simple and effective greedy algorithm for generating multiple codes with improved performance is devised increasing the practicality of this waveform family, and numerical results are provided to support the theoretical ones.

Inverse stochastic resonance in Izhikevich neural motifs driven by Gaussian colored noise under electromagnetic induction

Inverse stochastic resonance (ISR) is a modality of nonlinear response to noise, there is the biggest inhibitory effect of noise on neural electrical activity when the ISR happens. In this paper, the discharge activity of a triple-neuron feed-forward-loop (FFL) motif is investigated under the Gaussian colored noise and electromagnetic induction, where the FFL motif is constructed by Izhikevich neurons and connected by chemical synapse and the FFL motifs are classified into four types by the character of synaptic current. Here, the ISR induced by the Gaussian colored noise and electromagnetic induction is focused and various effects of different system parameters on ISR have been found. The most prominent ISR phenomenon will be seen in the case of low-input current and low cross-correlation ratio. There are no significant differences in the ISR curves for various chemical coupling strengths and chemical synapse delays, which conforms to the dynamic mechanisms of the ISR behavior. Besides, the ISR phenomenon also ensues under low electromagnetic induction levels and the effects of electromagnetic induction on the ISR are discussed. The results found here provide a novel perspective about the inhibitory effect on neural motif, which might help the biologists and pathologists understand some complex physiological phenomena of the nervous systems.