Recent years have seen a general resurgence of interest in analog signal processing and computing architectures. In addition, extensive theoretical and experimental literature on chaos and analog chaotic oscillators exists. One peculiarity of these circuits is the ability to generate, despite their structural simplicity, complex spatiotemporal patterns when several of them are brought towards synchronization via coupling mechanisms. While by no means a systematic survey, this paper provides a personal perspective on this area. After briefly covering design aspects and the synchronization phenomena that can arise, a selection of results exemplifying potential applications is presented, including in robot control, distributed sensing, reservoir computing, and data augmentation. Despite their interesting properties, the industrial applications of these circuits remain largely to be realized, seemingly due to a variety of technical and organizational factors including a paucity of design and optimization techniques. Some reflections are given regarding this situation, the potential relevance to discontinuous innovation in analog circuit design of chaotic oscillators taken both individually and as synchronized networks, and the factors holding back the transition to higher levels of technology readiness.

There has been a growing interest in the application of radar technology to the monitoring of humans and animals and their positions, motions, activities, and vital signs. Radar can be used, for example, to remotely measure vital signs such as respiration and heartbeat without contact. Radar-based human sensing is expected to be adopted in a variety of fields, such as medicine, healthcare, and entertainment, but what can be realized by radar-based animal sensing? This paper reviews the latest research trends in the noncontact sensing of animals using radar systems. We also present examples of our past radar experiments for the respiratory measurement of monkeys and the heartbeat measurement of chimpanzees. The trends in this field are reviewed in terms of the target animal species, type of vital sign, and radar type and selection of frequencies.

Low signal power and susceptibility to interference cause difficulties for traditional global navigation satellite system (GNSS) receivers in tracking weak signals. Extending coherent integration time is a common approach for enhancing signal gain. However, coherent integration time cannot be indefinitely increased owing to navigation bit sign transition, receiver dynamics, and clock noises. This study proposes a cross-correlation phase combining (CPC) algorithm suitable for distributed multi-antenna receivers to improve carrier-tracking performance in weak GNSS signal conditions. This algorithm cross-correlates each antenna’s intermediate frequency (IF) signal and local carrier to detect the phase differences. Subsequently, the IF signals are weighted to achieve phase alignment and coherently combined. The carrier-to-noise ratio (CNR) and carrier phase equation of the combined signal were derived for the CPC algorithm. Global positioning system (GPS) signals received by distributed antenna array with six elements were used to validate the performance of the algorithm. The results demonstrated that the CPC algorithm could effectively achieve signal phase alignment at 32 dB-Hz, resulting in a combined-signal CNR enhancement of 6 dB. The phase-tracking error variance was reduced by 72% at 30 dB-Hz compared with that of a single-antenna signal. The algorithm exhibited low phased array calibration requirements, overcoming the limitations associated with coherent integration time and effectively enhancing tracking performance in weak-signal environments.

High altitude platform (HAP), known as line-of-sight dominated communications, effectively enhance the spectral efficiency of wireless networks. However, the line-of-sight links, particularly in urban areas, may be severely deteriorated due to the complex communication environment. The reconfigurable intelligent surface (RIS) is employed to establish the cascaded-link and improve the quality of communication service by smartly reflecting the signals received from HAP to users without direct-link. Motivated by this, the joint precoding scheme for a novel RIS-aided beamspace HAP with non-orthogonal multiple access (HAP-NOMA) system is investigated to maximize the minimum user signal-to-leakage-plus-noise ratio (SLNR) by considering user fairness. Specifically, the SLNR is utilized as metric to design the joint precoding algorithm for a lower complexity, because the isolation between the precoding obtainment and power allocation can make the two parts be attained iteratively. To deal with the formulated non-convex problem, we first derive the statistical upper bound on SLNR based on the random matrix theory in large scale antenna array. Then, the closed-form expressions of power matrix and passive precoding matrix are given by introducing auxiliary variables based on the derived upper bound on SLNR. The proposed joint precoding only depends on the statistical channel state information (SCSI) instead of instantaneous channel state information (ICSI). NOMA serves multi-users simultaneously in the same group to compensate for the loss of spectral efficiency resulted from the beamspace HAP. Numerical results show the effectiveness of the derived statistical upper bound on SLNR and the performance enhancement of the proposed joint precoding algorithm.

Watermarking methods require robustness against various attacks. Conventional watermarking methods use error-correcting codes or spread spectrum to correct watermarking errors. Errors can also be reduced by embedding the watermark into the frequency domain and by using SIFT feature points. If the type and strength of the attack can be estimated, the errors can be further reduced. There are several types of attacks, such as scaling, rotation, and cropping, and it is necessary to aim for robustness against all of them. Focusing on the scaling tolerance of watermarks, we propose a watermarking method using SIFT feature points and DFT, and introduce a pilot signal. The proposed method estimates the scaling rate using the pilot signal in the form of a grid. When a stego-image is scaled, the grid interval of the pilot signal also changes, and the scaling rate can be estimated from the amount of change. The accuracy of estimating the scaling rate by the proposed method was evaluated in terms of the relative error of the scaling rate. The results show that the proposed method could reduce errors in the watermark by using the estimated scaling rate.

In recent years, blockchain has been widely applied in the Internet of Things (IoT). Blockchain oracle, as a bridge for data communication between blockchain and off-chain, has also received significant attention. However, the numerous and heterogeneous devices in the IoT pose great challenges to the efficiency and security of data acquisition for oracles. We find that the matching relationship between data sources and oracle nodes greatly affects the efficiency and service quality of the entire oracle system. To address these issues, this paper proposes a distributed and efficient oracle solution tailored for the IoT, enabling fast acquisition of real-time off-chain data. Specifically, we first design a distributed oracle architecture that combines both Trusted Execution Environment (TEE) devices and ordinary devices to improve system scalability, considering the heterogeneity of IoT devices. Secondly, based on the trusted node information provided by TEE, we determine the matching relationship between nodes and data sources, assigning appropriate nodes for tasks to enhance system efficiency. Through simulation experiments, our proposed solution has been shown to effectively improve the efficiency and service quality of the system, reducing the average response time by approximately 9.92% compared to conventional approaches.

Radar emitter identification (REI) is a crucial function of electronic radar warfare support systems. The challenge emphasizes identifying and locating unique transmitters, avoiding potential threats, and preparing countermeasures. Due to the remarkable effectiveness of deep learning (DL) in uncovering latent features within data and performing classifications, deep neural networks (DNNs) have seen widespread application in radar emitter identification (REI). In many real-world scenarios, obtaining a large number of annotated radar transmitter samples for training identification models is essential yet challenging. Given the issues of insufficient labeled datasets and abundant unlabeled training datasets, we propose a novel REI method based on a semi-supervised learning (SSL) framework with virtual adversarial training (VAT). Specifically, two objective functions are designed to extract the semantic features of radar signals: computing cross-entropy loss for labeled samples and virtual adversarial training loss for all samples. Additionally, a pseudo-labeling approach is employed for unlabeled samples. The proposed VAT-based SS-REI method is evaluated on a radar dataset. Simulation results indicate that the proposed VAT-based SS-REI method outperforms the latest SS-REI method in recognition performance.

This study investigates a two/three-dimensional (2D/3D) symbol-mapping technique that evaluates data transmission quality based on a four-level pulse-amplitude modulation (PAM-4) symbol transition. Multi-dimensional symbol transition mapping facilitates the visualization of the degree of interference (ISI). The simulation and experimental results demonstrated that the 2D symbol mapping can evaluate the PAM-4 data transmission quality degraded by ISI and visualize the equalization effect. Furthermore, potential applications of 2D mapping and its extension to 3D mapping were explored.

In high-speed data communication systems, it is important to evaluate the quality of the transmitted signal at the receiver. At a high-speed data rate, the transmission line characteristics act as a high-frequency attenuator and contribute to the intersymbol interference (ISI) at the receiver. To evaluate ISI conditions, eye diagrams are widely used to analyze signal quality and visualize the ISI effect as an eye-opening rate. Various types of on-chip eye-opening monitors (EOM) have been proposed to adjust waveform-shaping circuits. However, the eye diagram evaluation of multi-valued signaling becomes more difficult than that of binary transmission because of the complicated signal transition patterns. Moreover, in severe ISI situations where the eye is completely closed, eye diagram evaluation does not work well. This paper presents a novel evaluation method using Two-dimensional(2D) symbol mapping and a linear mixture model (LMM) for multi-valued data transmission. In our proposed method, ISI evaluation can be realized by 2D symbol mapping, and an efficient quantitative analysis can be realized using the LMM. An experimental demonstration of four leveled pulse amplitude modulation(PAM-4) data transmission using a Cat5e cable 100 m is presented. The experimental results show that the proposed method can extract features of the ISI effect even though the eye is completely closed in the server condition.

Signal processing using delta-sigma modulated bit streams is reviewed, along with related topics in stochastic computing (SC). The basic signal processing circuits, adders and multipliers, are covered. In particular, the possibility of preserving the noise-shaping properties inherent in delta-sigma modulation during these operations is discussed. Finally, the root mean square error for addition and multiplication is evaluated, and the performance improvement of signal processing in the delta-sigma domain compared with SC is verified.

High Frequency Surface Wave Radar holds significant potential in sea detection. However, the target signals are often surpassed by substantial sea clutter and ionospheric clutter, making it crucial to address clutter suppression and extract weak target signals amidst the strong noise background.This study proposes a novel method for separating weak harmonic target signals based on local tangent space, leveraging the chaotic feature of ionospheric clutter.The effectiveness of this approach is demonstrated through the analysis of measured data, thereby validating its practicality and potential for real-world applications.

In future deep space communication missions, VLBI (Very Long Baseline Interferometry) based on antenna array technology remains a critical detection method, which urgently requires the improvement of synthesis performance for antenna array signals. Considering this, focusing on optimizing the traditional antenna grouping method applied in the phase estimation algorithm, this letter proposes a “L/2 to L/2” antenna grouping method based on the maximum correlation signal-to-noise ratio (SNR). Following this idea, a phase difference estimation algorithm named “Couple” is presented. Theoretical analysis and simulation verification illustrate that: when ρ ＜ -10dB, the proposed “Couple” has the highest performance; increasing the number of antennas can significantly improve its synthetic loss performance and robustness. The research of this letter indicates a promising potential in supporting the rising deep space exploration and communication missions.

Space is becoming increasingly congested and contested, which calls for effective means to conduct effective monitoring of high-value space assets, especially in Space Situational Awareness (SSA) missions, while there are imperfections in existing methods and corresponding algorithms. To overcome such a problem, this letter proposes an algorithm for accurate Connected Element Interferometry (CEI) in SSA based on more interpolation information and iterations. Simulation results show that: (i) after iterations, the estimated asymptotic variance of the proposed method can basically achieve uniform convergence, and the ratio of it to ACRB is 1.00235 in δ0 ∈ [-0.5, 0.5], which is closer to 1 than the current best AM algorithms; (ii) In the interval of SNR ∈ [-14dB, 0dB], the estimation error of the proposed algorithm decreases significantly, which is basically comparable to CRLB (maintains at 1.236 times). The research of this letter could play a significant role in effective monitoring and high-precision tracking and measurement with significant space targets during futuristic SSA missions.

The existing discrete-logarithm-based two-round multi-signature schemes without using the idealized model, i.e., the Algebraic Group Model (AGM), have quite large reduction loss. This means that an implementation of these schemes requires an elliptic curve (EC) with a very large order for the standard 128-bit security when we consider concrete security. Indeed, the existing standardized ECs have orders too small to ensure 128-bit security of such schemes. Recently, Pan and Wagner proposed two two-round schemes based on the Decisional Diffie-Hellman (DDH) assumption (EUROCRYPT 2023). For 128-bit security in concrete security, the first scheme can use the NIST-standardized EC P-256 and the second can use P-384. However, with these parameter choices, they do not improve the signature size and the communication complexity over the existing non-tight schemes. Therefore, there is no two-round scheme that (i) can use a standardized EC for 128-bit security and (ii) has high efficiency. In this paper, we construct a two-round multi-signature scheme achieving both of them from the DDH assumption. We prove that an EC with at least a 321-bit order is sufficient for our scheme to ensure 128-bit security. Thus, we can use the NIST-standardized EC P-384 for 128-bit security. Moreover, the signature size and the communication complexity per one signer of our proposed scheme under P-384 are 1152 bits and 1535 bits, respectively. These are most efficient among the existing two-round schemes without using the AGM including Pan-Wagner’s schemes and non-tight schemes which do not use the AGM. Our experiment on an ordinary machine shows that for signing and verification, each can be completed in about 65 ms under 100 signers. This shows that our scheme has sufficiently reasonable running time in practice.

A 0.13mJ/prediction with 68.6% accuracy wired-logic deep neural network (DNN) processor is developed in a single 16-nm field-programmable gate array (FPGA) chip. Compared with conventional von-Neumann architecture DNN processors, the energy efficiency is greatly improved by eliminating DRAM/BRAM access. A technical challenge for conventional wired-logic processors is the large amount of hardware resources required for implementing large-scale neural networks. To implement a large-scale convolutional neural network (CNN) into a single FPGA chip, two technologies are introduced: (1) a sparse neural network known as a non-linear neural network (NNN), and (2) a newly developed raster-scan wired-logic architecture. Furthermore, a novel high-level synthesis (HLS) technique for wired-logic processor is proposed. The proposed HLS technique enables the automatic generation of two key components: (1) Verilog-hardware description language (HDL) code for a raster-scan-based wired-logic processor and (2) test bench code for conducting equivalence checking. The automated process significantly mitigates the time and effort required for implementation and debugging. Compared with the state-of-the-art FPGA-based processor, 238 times better energy efficiency is achieved with only a slight decrease in accuracy on the CIFAR-100 task. In addition, 7 times better energy efficiency is achieved compared with the state-of-the-art network-optimized application-specific integrated circuit (ASIC).

The subject must be motionless for conventional radar-based non-contact vital signs measurements. Additionally, the measurement range is limited by the design of the radar module itself. Although the accuracy of measurements has been improving, the prospects for their application could have been faster to develop. This paper proposed a novel radar-based adaptive tracking method for measuring the heart rate of the moving monitored person. The radar module is fixed on a circular plate and driven by stepping motors to rotate it. In order to protect the user’s privacy, the method uses radar signal processing to detect the subject’s position to control a stepping motor that adjusts the radar’s measurement range. The results of the fixed-route experiments revealed that when the subject was moving at a speed of 0.5 m/s, the mean values of RMSE for heart rate measurements were all below 2.85 beat per minute (bpm), and when moving at a speed of 1 m/s, they were all below 4.05 bpm. When subjects walked at random routes and speeds, the RMSE of the measurements were all below 6.85 bpm, with a mean value of 4.35 bpm. The average RR interval time of the reconstructed heartbeat signal was highly correlated with the electrocardiography (ECG) data, with a correlation coefficient of 0.9905. In addition, this study not only evaluated the potential effect of arm swing (more normal walking motion) on heart rate measurement but also demonstrated the ability of the proposed method to measure heart rate in a multiple-people scenario.

Webpage texts are often emphasized by decorations such as bold, italic, underline, and text color using HTML (HyperText Markup Language) tags and CSS (Cascading Style Sheets). However, users with visual impairment often struggle to recognize decorations appropriately because most screen readers do not read decorations appropriately. To overcome this limitation, we propose a method to read emphasized texts by changing the reading voice parameters of a screen reader and adding sound effects. First, the strong emphasis types and reading voices are investigated. Second, the intensity of the emphasis type is used to calculate a score. Then the score is used to assign the reading method for the emphasized text. Finally, the proposed method is evaluated by users with and without visual impairment. The proposed method can convey emphasized texts, but future improvements are necessary.

A method for bandwidth enhancement of radar cross section (RCS) reduction by metasurfaces was studied. Scattering cancellation is one of common methods for reducing RCS of target scatterers. It occurs when the wave scattered by the target scatterer and the wave scattered by the canceling scatterer are the same amplitude and opposite phase. Since bandwidth of scattering cancellation is usually narrow, we proposed the bandwidth enhancement method using metasurfaces, which can control the frequency dependence of the scattering phase. We designed and fabricated a metasurface composed of a patch array on a grounded dielectric substrate. Numerical and experimental evaluations confirmed that the metasurface enhances the bandwidth of 10dB RCS reduction by 52% bandwidth ratio of the metasurface from 34% bandwidth ratio of metallic cancelling scatterers.

We study a visible light communication (VLC) system that modulates data signals by changing the color components of image contents on a digital signage display, captures them with an image sensor, and demodulates them using image processing. This system requires that the modulated data signals should not be perceived by the human eye. Previous studies have proposed modulation methods with a chromaticity component that is difficult for the human eye to perceive, and we have also proposed a modulation method with perceptually uniform color space based on human perception characteristics. However, which chromaticity component performs better depends on the image contents, and the evaluation only for some specific image contents was not sufficient. In this paper, we evaluate the communication and visual quality of the modulation methods with chromaticity components for various standard images to clarify the superiority of the method with perceptually uniform color space. In addition, we propose a novel modulation and demodulation method using diversity combining to eliminate the dependency of performance on the image contents. Experimental results show that the proposed method can improve the communication and visual quality for almost all the standard images.

Fault-tolerant aggregate signature (FT-AS) is a special type of aggregate signature that is equipped with the functionality for tracing signers who generated invalid signatures in the case an aggregate signature is detected as invalid. In existing FT-AS schemes (whose tracing functionality requires multi-rounds), a verifier needs to send a feedback to an aggregator for efficiently tracing the invalid signer(s). However, in practice, if this feedback is not responded to the aggregator in a sufficiently fast and timely manner, the tracing process will fail. Therefore, it is important to estimate whether this feedback can be responded and received in time on a real system. In this work, we measure the total processing time required for the feedback by implementing an existing FT-AS scheme, and evaluate whether the scheme works without problems in real systems. Our experimental results show that the time required for the feedback is 605.3 ms for a typical parameter setting, which indicates that if the acceptable feedback time is significantly larger than a few hundred ms, the existing FT-AS scheme would effectively work in such systems. However, there are situations where such feedback time is not acceptable, in which case the existing FT-AS scheme cannot be used. Therefore, we further propose a novel FT-AS scheme that does not require any feedback. We also implement our new scheme and show that a feedback in this scheme is completely eliminated but the size of its aggregate signature (affecting the communication cost from the aggregator to the verifier) is 144.9 times larger than that of the existing FT-AS scheme (with feedbacks) for a typical parameter setting, and thus has a trade-off between the feedback waiting time and the communication cost from the verifier to the aggregator with the existing FT-AS scheme.