Modulation Patterns Research Articles

Modulation recognition of optical and electromagnetic waves based on transfer learning

Light is a type of electromagnetic wave. Research on the modulation recognition of communication signals, which are also electromagnetic waves, can be applied to the field of modulation and demodulation of optical waves. The limited signal data and varying data distribution have an impact on the automatic modulation recognition of signals. To address this, we proposed a method to enhance the characteristic information of modulation patterns carried by signal data. We used the Wigner–Ville distribution and short-time Fourier transform to convert the original I/Q multi-channel modulated communication signal into time–frequency representation images (TFRIs). Additionally, we adopted a transfer learning approach, the domain adaptation network (DAN), to identify modulation modes of signals under different SNRs. The combination of signal conversion and transfer learning significantly improved the identification of modulation recognition. Our experiments demonstrated that our proposed method outperformed existing state-of-the-art methods in terms of classification accuracy at both high and low signal-to-noise ratios (SNRs). Specifically, our method achieved a 10% increase in Top1-accuracy under high SNR, and overall improved the classification accuracy under low SNR compared to the adversarial transfer learning architecture (ATLA). This is attributed to the use of a more diverse and accurate dataset that provides a better representation of real-world communication signals. We also compared our experimental results with those of other papers, and the results show that our method achieved the best performance among the current state-of-the-art methods, considering the classification accuracy at different SNRs.

Sparse Adversarial Attacks against DL-Based Automatic Modulation Classification

Automatic modulation recognition (AMR) serves as a crucial component in domains such as cognitive radio and electromagnetic countermeasures, acting as a significant prerequisite for the efficient signal processing of receivers. Deep neural networks (DNNs), despite their effectiveness, are known to be vulnerable to adversarial attacks. This vulnerability has inspired the introduction of subtle interference to wireless communication signals—interference so minuscule that it is difficult for the human eye to discern. Such interference can mislead eavesdroppers into erroneous modulation pattern recognition when using DNNs, thereby camouflaging communication signal modulation patterns. Nonetheless, the majority of current camouflage methods used for electromagnetic signal modulation recognition rely on a global perturbation of the signal. They fail to consider the local agility of signal disturbance and the concealment requirements for bait signals that are intercepted by the interceptor. This paper presents a generator framework designed to produce perturbations with sparse properties. Furthermore, we introduce a method to reduce spectral loss, which minimizes the spectral difference between adversarial perturbation and the original signal. This method makes perturbation more challenging to monitor, thereby deceiving enemy electromagnetic signal modulation recognition systems. The experimental results validated that the proposed method significantly outperformed existing methods in terms of generation time. Moreover, it can generate adversarial signals characterized by high deceivability and transferability even under extremely sparse conditions.

Investigation of Soft-Switching QSW Technique in DC/DC SiC-Based Flying Capacitor Converter With Q2L Control

This paper investigates the soft-switching quasi-square-wave (QSW) technique in DC/DC SiC-based flying capacitor converter with quasi-two-level (Q2L) control establishing design guidelines for constructing high-efficiency soft-switched bidirectional converters with low-voltage power transistors. The general idea behind the soft-switching in the proposed system is based on near-CRM (critical conduction mode) operation using TCM (triangular current mode) and Q2L control with the addition of auxiliary transistor capacitances. The soft-switching process is based on a resonance between the capacitances in parallel to each transistor, and the main inductor - ZVS at turn-on is ensured through proper modulation pattern according to TCM-Q2L control, and the turn-off soft-switching mechanism is assured through the novelty in the form of adding auxiliary capacitance in parallel to each of the SiC power MOSFETs according to QSW operation. Thus, the converter can reach very high efficiency (peak at 99.5%), maintaining soft-switching for a wide operating range, using only small auxiliary SMD capacitors and a low-volume flying capacitor, leading to high power density. The presented study is based on experimental tests using a 1.5 kV model at up to 15 kW and includes the impact of various auxiliary capacitance values and optimal capacitor value selection for maximizing the converter efficiency.

Nonlinear localized wave modes in optomechanical array

Abstract Optomechanical arrays have been used in many areas of research, from nonlinear optics to acoustics. In particular, the optomechanical array has been studied for its interesting properties such as strong optical force and high frequency resonance. In this work, we carry out the modulated wave patterns and nonlinear modes by driving one end of the optomechanical array in the forbidden gap. We use the discrete nonlinear Schrödinger equation with self-Kerr nonlinear term to determine the threshold amplitude. We then consider the driven amplitude to drive the model above the phonon band. The result is a train of waves with an asymmetric shape in the forbidden gap. For large values of the nonlinear term, we observe unstable modes of the modulation growth rates and the modulated wave patterns also emerge from the driven optomechanical array. At the specific cell index, the pulse train increases in amplitude and brings instability in the bandgap. These results open a new feature of the position modulated self-Kerr nonlinear term as an internal force to drive the nonlinear Schrödinger equation.

Rotationally synchronized single-pixel imaging for a fast-rotating object

In practical application environments, objects are rarely stationary, which makes it difficult to image dynamic objects with conventional single-pixel imaging (SI) techniques. In this paper, a rotationally synchronized single-pixel imaging (RS-SI) method is proposed to image a dynamic object in rotation. The modulation pattern rotates in sync with the rapidly rotating object, and the center of object rotation is ensured to be in line with the center of the illumination pattern. Then, RS-SI reconstruction algorithm is used to reconstruct the image of the rotating object by collecting the light reflected from the object's surface. This method does not require advanced knowledge of the object rotation speed to complete the imaging. Simulation and experimental results confirm that the RS-SI can reconstruct images of an object at rotational speeds up to 422.0 rpm and can also complete imaging of a variable-speed rotating object. Imaging results of 128 × 128 pixels at a sampling rate of 27.47% can be obtained with high fidelity. The proposed RS-SI is a method for imaging an object in rotation, providing insights for future applications of single-pixel imaging technology for defect detection in rotating parts.

Masked autoencoder for highly compressed single-pixel imaging.

The single-pixel imaging technique uses multiple patterns to modulate the entire scene and then reconstructs a two-dimensional (2-D) image from the single-pixel measurements. Inspired by the statistical redundancy of natural images that distinct regions of an image contain similar information, we report a highly compressed single-pixel imaging technique with a decreased sampling ratio. This technique superimposes an occluded mask onto modulation patterns, realizing that only the unmasked region of the scene is modulated and acquired. In this way, we can effectively decrease 75% modulation patterns experimentally. To reconstruct the entire image, we designed a highly sparse input and extrapolation network consisting of two modules: the first module reconstructs the unmasked region from one-dimensional (1-D) measurements, and the second module recovers the entire scene image by extrapolation from the neighboring unmasked region. Simulation and experimental results validate that sampling 25% of the region is enough to reconstruct the whole scene. Our technique exhibits significant improvements in peak signal-to-noise ratio (PSNR) of 1.5 dB and structural similarity index measure (SSIM) of 0.2 when compared with conventional methods at the same sampling ratios. The proposed technique can be widely applied in various resource-limited platforms and occluded scene imaging.

Electrically controlled hybrid superconductor–ferromagnet cell for high density cryogenic memory

We report the fabrication and testing, at 4.2 K, of an S1IS2FS3 device, where S, F, and I denote a superconductor (Nb), a ferromagnetic material (Permalloy), and an insulator (AlOx), respectively. The F layer covers about one half of the top electrode of the S1IS2 Josephson junction and is positioned off-center. Electric current, Itr, along the S3 electrode can change the magnetization of the F layer in such a way that, for one direction of Itr, a magnetic flux penetrates the junction perpendicular to the layers, whereas for the opposite direction, the perpendicular magnetic flux can be removed. In the former state, the modulation pattern of the Josephson critical current, Ic, in the magnetic field, H, may acquire minimum near H = 0 and restores its usual shape with maximum in the second state. These states can be used for building a compact cryogenic memory compatible with single flux quantum electronics.

Arousal modulates the amygdala-insula reciprocal connectivity during naturalistic emotional movie watching

Emotional arousal is a complex state recruiting distributed cortical and subcortical structures, in which the amygdala and insula play an important role. Although previous neuroimaging studies have showed that the amygdala and insula manifest reciprocal connectivity, the effective connectivities and modulatory patterns on the amygdala-insula interactions underpinning arousal are still largely unknown. One of the reasons may be attributed to static and discrete laboratory brain imaging paradigms used in most existing studies. In this study, by integrating naturalistic-paradigm (i.e., movie watching) functional magnetic resonance imaging (fMRI) with a computational affective model that predicts dynamic arousal for the movie stimuli, we investigated the effective amygdala-insula interactions and the modulatory effect of the input arousal on the effective connections. Specifically, the predicted dynamic arousal of the movie served as regressors in general linear model (GLM) analysis and brain activations were identified accordingly. The regions of interest (i.e., the bilateral amygdala and insula) were localized according to the GLM activation map. The effective connectivity and modulatory effect were then inferred by using dynamic causal modeling (DCM). Our experimental results demonstrated that amygdala was the site of driving arousal input and arousal had a modulatory effect on the reciprocal connections between amygdala and insula. Our study provides novel evidence to the underlying neural mechanisms of arousal in a dynamical naturalistic setting.

Sound non-reciprocity based on synthetic magnetism

Synthetic magnetism has been recently realized using spatiotemporal modulation patterns, producing non-reciprocal steering of charge-neutral particles such as photons and phonons. Here, we design and experimentally demonstrate a non-reciprocal acoustic system composed of three compact cavities interlinked with both dynamic and static couplings, in which phase-correlated modulations induce a synthetic magnetic flux that breaks time-reversal symmetry. Within the rotating wave approximation, the transport properties of the system are controlled to efficiently realize large non-reciprocal acoustic transport. By optimizing the coupling strengths and modulation phases, we achieve frequency-preserved unidirectional transport with 45-dB isolation ratio and 0.85 forward transmission. Our results open to the realization of acoustic non-reciprocal technologies with high efficiency and large isolation, and offer a route towards Floquet topological insulators for sound.

Analysis of the Effect of 0-π SQUIDs for Enhancing Mutual Coupling

This study shows that we can obtain an enhanced mutual coupling by using a superconducting quantum interference device (SQUID) containing a π-phase shift Josephson junction (π-junction). The π-junction can increase the current flowing in the loop inductance of the SQUID, thereby enhancing the magnetic flux generated in the inductance. Therefore, the effective self-inductance of the SQUID can increase, resulting in an increase in the mutual coupling. We use a 0-π SQUID formed by a conventional Josephson junction (0-junction) and a π-junction. Our numerical analysis for a simplified structure revealed that the ratio of effective to original self-inductance increased to 50. To confirm this, we measured the modulation patterns of critical current in dc-SQUIDs in which part of the loop inductance was replaced with a series of 0-π SQUIDs. The observed modulation pattern revealed that the effective self-inductance became more than 10-fold larger than the original self-inductance under the conditions that the applied current is a few μA while the critical current of the 0-junction in 0-π SQUIDs is 35 μA.

Sub-GHz resolution line-by-line pulse shaper for driving superconducting circuits

We demonstrate a sub-GHz resolution, fully programmable Fourier-domain pulse shaper capable of generating arbitrary optical pulse patterns for superconducting circuit platforms. This high resolution allows line-by-line pulse shaping of a 1 GHz-spaced comb, and the pulse shaper can accommodate an optical bandwidth as large as 1 THz, which represents the highest resolution programmable line-by-line pulse shaping to our knowledge. Linear optical sampling with a dual-comb system confirms independent control of 1 GHz-spaced optical lines, and the low phase noise of the pulse shaper is characterized. We apply the pulse shaper as an optical drive for an array of Josephson junctions operating at a temperature of 4 K, where cryogenic photodetection of pulse doublets with user-defined separation characterizes the Josephson junction response. Furthermore, we demonstrate a pulse-density modulation pattern of 4 ps duration optical pulses that can serve as the high bandwidth drive of a quantum-based Josephson arbitrary waveform synthesizer. By leveraging the exquisite control, large bandwidth, and low noise of photonics, this represents an important advance toward the realization of high power and high spectral purity AC voltage standards at gigahertz frequencies without requiring 100 GHz bandwidth driving electronics.

Provocation of verbal interaction of dolphins via a hydro-acoustic channel on the basis of cognitive empathy

The provocation of the hydroacoustic communication interaction of Tursiops truncatus dolphins based on cognitive empathy showed that they use packets of ultrashort pulses (USPs) in the process of “dialogue”. The duration of bursts varies from 40 ms to 3000 ms with modulation of the interval between USPs from ~1 to ~120 ms and pauses between bursts. The interval modulation pattern is structured using various modulation laws. The communication signals were obtained in an experiment with theparticipation of three animals, who knew the main task of sequential acoustic differentiation of two objective stimuli. The impetus for hydroacoustic interaction is the resolution of uncertainty when teaching the respondent the inverse differentiation problem. This generates emotional empathy in observers and provokes vocalization between individuals. The advantages and disadvantages of methodological methods of provoking hydroacoustic interaction are considered in detail, starting the process of cognitive empathy. In the method under consideration, echolocation and communication signals are spaced apart in time and space, which allows them to be uniquely identified.

Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb.

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

Determining carrier-envelope phase of an ultrashort laser pulse in quantum well via tuning inhomogeneity

When a few-cycle Inhomogeneous laser pulse propagates in parabolic quantum wells, a soliton pulse can occur after a certain propagation distance. The duration and peak intensity of such a soliton pulse are both sensitively dependent on the carrier-envelope phase (CEP) of the incident few-cycle pulse. This kind of CEP-dependence follows a sinusoidal modulation pattern with the Inhomogeneous degree of the incident laser field, which provides a route to determine the CEP by just shaping the field's inhomogeneity analogous to that by using polar media.

Amplitude modulation pattern of rat distress vocalisations during fear conditioning

In humans, screams have strong amplitude modulations (AM) at 30 to 150 Hz. These AM correspond to the acoustic correlate of perceptual roughness. In bats, distress calls can carry AMs, which elicit heart rate increases in playback experiments. Whether amplitude modulation occurs in fearful vocalisations of other animal species beyond humans and bats remains unknown. Here we analysed the AM pattern of rats’ 22-kHz ultrasonic vocalisations emitted in a fear conditioning task. We found that the number of vocalisations decreases during the presentation of conditioned stimuli. We also observed that AMs do occur in rat 22-kHz vocalisations. AMs are stronger during the presentation of conditioned stimuli, and during escape behaviour compared to freezing. Our results suggest that the presence of AMs in vocalisations emitted could reflect the animal’s internal state of fear related to avoidance behaviour.

Modulation instability gain and localized waves in the modified Frenkel–Kontorova model with high-order nonlinearities

In this paper, modulation instability and nonlinear supratransmission are investigated in a one-dimensional chain of atoms using cubic–quartic nonlinearity coefficients. As a result, we establish the discrete nonlinear evolution equation by using the multi-scale scheme. To compute the modulation instability gain, the linearizing technique is employed. The effect of the higher nonlinear component on modulation instability is particularly examined. Following that, full numerical integration was performed to identify modulated wave patterns as well as the appearance of a rogue wave. Through the nonlinear supratransmission phenomenon, one end of the discrete model is driven into the forbidden bandgap. As a consequence, for driving amplitudes above the supratransmission threshold, the bright soliton and modulated wave patterns are satisfied. An important behavior is observed in the transient range of time of propagation when the bright soliton wave turns into a chaotic soliton wave. These results corroborate our analytical investigations on the modulation instability and show that the one-dimensional chain of atoms is a fruitful medium to generate long-lived modulated waves.

Innovative Pre-Clinical Data Using Peptides to Intervene in the Evolution of Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, relentless, and deadly disease. Little is known about its pathogenetic mechanisms; therefore, developing efficient pharmacological therapies is challenging. This work aimed to apply a therapeutic alternative using immunomodulatory peptides in a chronic pulmonary fibrosis murine model. BALB/c mice were intratracheally instilled with bleomycin (BLM) and followed for 30 days. The mice were treated with the immune modulatory peptides ToAP3 and ToAP4 every three days, starting on the 5th day post-BLM instillation. ELISA, qPCR, morphology, and respiratory function analyses were performed. The treatment with both peptides delayed the inflammatory process observed in the non-treated group, which showed a fibrotic process with alterations in the production of collagen I, III, and IV that were associated with significant alterations in their ventilatory mechanics. The ToAP3 and ToAP4 treatments, by lung gene modulation patterns, indicated that distinct mechanisms determine the action of peptides. Both peptides controlled the experimental IPF, maintaining the tissue characteristics and standard function properties and regulating fibrotic-associated cytokine production. Data obtained in this work show that the immune response regulation by ToAP3 and ToAP4 can control the alterations that cause the fibrotic process after BLM instillation, making both peptides potential therapeutic alternatives and/or adjuvants for IPF.

Decadal changes in rapid intensification of western North Pacific tropical cyclones modulated by the North Pacific Gyre Oscillation

This study investigates the modulation of western North Pacific (WNP) tropical cyclone rapid intensification (RI) by the North Pacific Gyre Oscillation (NPGO) on decadal timescales. There is a significant inverse relationship between basinwide RI numbers during July–November and the simultaneous NPGO index from 1970 to 2021. During the positive NPGO phase, suppressed RI occurs over almost the entire WNP, with a distinctly different spatial distribution compared to the Pacific Decadal Oscillation-driven pattern of RI modulation. RI occurrence is significantly reduced over the eastern Philippine Sea (10°–25°N, 140°–155°E). This is primarily caused by enhanced negative low-level vorticity, which can be linked to the horizontal extent of the anomalous low-level anticyclone. By comparison, over the western Philippine Sea (10°–25°N, 125°–140°E), there are only weak RI occurrence changes due to offsetting influences of increased mid-level humidity and decreased low-level vorticity.

A Route to Ultra‐Fast Amplitude‐Only Spatial Light Modulation using Phase‐Change Materials

AbstractA phase‐change material based, thin‐film, amplitude‐only spatial light modulator is presented. The modulator operates in reflection and modulates the amplitude of light incident on its surface with no effect on optical phase when the phase‐change material is switched between its amorphous and crystalline states. This is achieved using a thin‐film device with an embedded, switchable, GeTe phase‐change layer. Test modulation patterns are written to the device using laser scans, and the amplitude and phase response measured, using optical spectroscopy and off‐axis digital holography. Experimental results reveal reflected intensity to be modulated by up to 38%, with an averaged phase difference of less than ≈π/50. Since phase‐change materials such as GeTe can be switched on sub‐microsecond timescales, this approach maps out a route for ultra‐fast amplitude spatial light modulators with widespread applications in fields such as wavefront shaping, communications, sensing, and imaging.

From Motivation to Action: Action Cost Better Predicts Changes in Premovement Beta-Band Activity than Speed.

Although premovement beta-band event-related desynchronization (β-ERD; 13-30 Hz) from sensorimotor regions is modulated by movement speed, current evidence does not support a strict monotonic association between the two. Given that β-ERD is thought to increase information encoding capacity, we tested the hypothesis that it might be related to the expected neurocomputational cost of movement, here referred to as action cost. Critically, action cost is greater both for slow and fast movements compared with a medium or "preferred" speed. Thirty-one right-handed participants performed a speed-controlled reaching task while recording their EEG. Results revealed potent modulations of beta power as a function of speed, with β-ERD being significantly greater both for movements performed at high and low speeds compared with medium speed. Interestingly, medium-speed movements were more often chosen by participants than low-speed and high-speed movements, suggesting that they were evaluated as less costly. In line with this, modeling of action cost revealed a pattern of modulation across speed conditions that strikingly resembled the one found for β-ERD. Indeed, linear mixed models showed that estimated action cost predicted variations of β-ERD significantly better than speed. This relationship with action cost was specific to beta power, as it was not found when averaging activity in the mu band (8-12 Hz) and gamma band (31-49 Hz) bands. These results demonstrate that increasing β-ERD may not merely speed up movements, but instead facilitate the preparation of high-speed and low-speed movements through the allocation of additional neural resources, thereby enabling flexible motor control.SIGNIFICANCE STATEMENT Heightened beta activity has been associated with movement slowing in Parkinson's disease, and modulations of beta activity are commonly used to decode movement parameters in brain-computer interfaces. Here we show that premovement beta activity is better explained by the neurocomputational cost of the action rather than its speed. Instead of being interpreted as a mere reflection of changes in movement speed, premovement changes in beta activity might therefore be used to infer the amount of neural resources that are allocated for motor planning.