Signal Processing Functions Research Articles

Electro-optic tunable optical filter based on long-period waveguide grating in lithium niobate on insulator with absorption ribbons.

We propose an electro-optic tunable optical filter based on sidewall long period waveguide grating (LPWG) in lithium niobate on insolator (LNOI). The operation of our proposed filter is based on the mode coupling, filtering, and absorption achieved, respectively, with two corrugated sidewall LPWGs, a tapered waveguide, and two metal ribbons. Our typical fabricated devices achieved a 16.32-dB rejection band and an EO tuning efficiency of ∼0.344 nm/V. Our proposed LPWG and filter are compact and could be integrated with other LNOI waveguide devices to realize more sophisticated functions for on-chip optical signal processing.

Construction of intelligent multi-construction management platform for bridges based on BIM technology

ABSTRACT In order to improve the efficiency of bridge intelligent multi-construction management, this paper combines BIM technology to build an intelligent multi-construction management platform for bridges, and studies the realization of vibration signal processing, feature extraction, fault diagnosis and wireless communication functions. Moreover, this paper completes the extraction of vibration signal features from three aspects: time domain, frequency domain and time–frequency domain, and manages the bridge construction process according to the extracted features. In addition, this paper establishes the integration between the bridge template design optimization module and the BIM model through the API interface of the Revit platform, realizes the extraction of design information from the BIM model of the bridge and combines template attribute information and safety design specifications to process it. From the simulation evaluation results, it can be seen that the bridge intelligent multi-construction management platform based on BIM technology proposed in this paper can effectively improve the management efficiency of bridge intelligent construction.

A Time-Domain Reconfigurable Second-Order Noise Shaping ADC With Single Fan-Out Gated Delay Cells

This brief proposes a time-domain second-order noise shaping analog-to-digital converter (ADC). It employs a voltage-to-time converter (VTC) in tandem with a second-order noise shaping time-to-digital converter (TDC), which realizes the goal of reducing the power consumption and accommodating different resolutions by configuring locations of poles of the transfer function. Note that the time-register constructed TDC, which performs the signal processing function in the time domain, is implemented with digital cells thoroughly. In this way, the proposed architecture can be more friendly to the increasingly scaled process. The reconfigurable architecture enables to obtain the target signal-to-noise-and-distortion ratio (SNDR) with decreased oversampling ratio (OSR), which improves energy efficiency relatively. In addition, compared with the conventional CMOS gated delay cell, the proposed single fan-out (SFO) gated delay cell is featured with lower power dissipation and shorter delaying time. The prototype is implemented in a 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\bm\mu$</tex-math> </inline-formula> m CMOS technology to demonstrate the validity of this proposed time-domain ADC. It achieves 64.5-, 56.1-, and 51.2-dB SNDR in 0.025-, 0.05-, and 0.1-MHz bandwidth on conditions of the OSR being 200, 100, and 50, respectively.

Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

Many speech processing systems struggle in conditions with low signal-to-noise ratios and in changing acoustic environments. Adaptation at the transduction level with integrated signal processing could help to address this; in human hearing, transduction and signal processing are integrated and can be adaptively tuned for noisy conditions. Here we report a microelectromechanical cochlea as a bio-inspired acoustic sensor with integrated signal processing functionality. Real-time feedback is used to tune the sensing and processing properties, and dynamic switching between linear and nonlinear characteristics improves the detection of signals in noisy conditions, increases the sensor dynamic range and enables adaptation to changing acoustic environments. The transition to nonlinear behaviour is attributed to a Hopf bifurcation and we experimentally validate its dependence on sensor and feedback parameters. We also show that output-signal coupling between two coupled sensors can increase the frequency coverage.

An Artificial Intelligence‐Motivated Skin‐Like Optical Fiber Tactile Sensor

Soft and stretchable tactile sensors have received extensive attention for their potential applications in wearables, human–robot interaction, and intelligent robots. Herein, inspired by the functions of skin somatosensory signal generation and processing, an artificial intelligence‐motivated skin‐like optical fiber tactile (SOFT) sensor is proposed. It features multifunctional touch interaction capabilities including tactile amplitude and position and tensile strain. Four fiber Bragg gratings (FBGs) are embedded in a skin‐like three‐layer laminate structure of the SOFT sensor, forming a flexible tactile sensing array with a stretchability larger than 20%. Fusing the two‐level cascaded neural network, the position and magnitude of the contact force can be distinguished simultaneously. The recognition accuracy for contact position is up to 92.41% and the error is less than 4.2% within the force range of 0–3.5 N. Several SOFT sensor‐based interactive applications including pressure password interface and music playback are achieved by combining the artificial intelligence spatiotemporal dynamic logic analysis. Furthermore, the sensor is also capable of complex scenes involving tension and tactile sensing, such as dexterous hand perception and human–robot interaction control. This work provides novel insights into artificial intelligence‐based integrated skin that shows broad promise in intelligent prosthetics and bionic robotic.

All-fibre phase filters with 1-GHz resolution for high-speed passive optical logic processing

Photonic-based implementation of advanced computing tasks is a potential alternative to mitigate the bandwidth limitations of electronics. Despite the inherent advantage of a large bandwidth, photonic systems are generally bulky and power-hungry. In this respect, all-pass spectral phase filters enable simultaneous ultrahigh speed operation and minimal power consumption for a wide range of signal processing functionalities. Yet, phase filters offering GHz to sub-GHz frequency resolution in practical, integrated platforms have remained elusive. We report a fibre Bragg grating-based phase filter with a record frequency resolution of 1 GHz, at least 10× improvement compared to a conventional optical waveshaper. The all-fibre phase filter is employed to experimentally realize high-speed fully passive NOT and XNOR logic operations. We demonstrate inversion of a 45-Gbps 127-bit random sequence with an energy consumption of ~34 fJ/bit, and XNOR logic at a bit rate of 10.25 Gbps consuming ~425 fJ/bit. The scalable implementation of phase filters provides a promising path towards widespread deployment of compact, low-energy-consuming signal processors.

State-Of-The-Art On Reversible Multiplier Architectures and Its Comparison for Future Quantum Computing

Multiplication is the key crucial operation in realizing digital signal processing (DSP) functions. It is accomplished by using diverse multiplier architectures. Multiplication operation is furthermost basic and normally used action in the central processing unit (CPU). The multiplication operation is the most fundamental and commonly performed activity in the central processing unit (CPU). An efficient multiplier design should have a high speed, small area, and a low power consumption. Compact, efficient multipliers with minimal power dissipation are needed. The proposed paper provides a thorough inspection of multipliers such as the Array multiplier, Booth multiplier, column bypass multiplier, Baugh-Wooley multiplier, and Vedic multiplier based on their operational activities and working, as well as their benefits and limits. A comparison of these multipliers' performance parameters such as speed, area, power consumption, quantum cost, garbage generation and circuit complexity.

Engineering Controllable Pulse Generation for Molecular Communication via Genetic Circuits

Synthetic biology provides the engineering community with a tool to build biological entities that are capable of carrying out desired signal processing functionalities. The design and study of genetic circuits that exhibit natural behavior can be helpful for an improved understanding of the principles and kinetics behind the gene expression behavior, as well as for engineering cellular systems for synthetic biology. In this paper, we propose a synthetic biology system capable of generating a pulse-shaped signal, which is a prevalent behavior in natural environment. In particular, our proposed pulse generation system divides the pulse generation functions into different cells which are connected by intercellular signaling molecules. More specifically, the system is consisted of three engineered cells with different digital logic functionalities, and the pulse generation exploits the alteration in logic state. To quantitatively describe the generated pulse, we not only analyze the individual behavior of each cell using Shea-Ackers formalism but also derive the intercellular signaling channel. Simulation results demonstrate that the pulse-shaped signal can be produced in a controllable manner by arranging cells in different spatial configurations.

A Self‐Powered, Rechargeable, and Wearable Hydrogel Patch for Wireless Gas Detection with Extraordinary Performance

AbstractFlexible gas sensors play an indispensable role in diverse applications spanning from environmental monitoring to portable medical electronics. Full wearable gas monitoring system requires the collaborative support of high‐performance sensors and miniaturized circuit module, whereas the realization of low power consumption and sustainable measurement is challenging. Here, a self‐powered and reusable all‐in‐one NO2 sensor is proposed by structurally and functionally coupling the sensor to the battery, with ultrahigh sensitivity (1.92%/ppb), linearity (R2 = 0.999), ultralow theoretical detection limit (0.1 ppb), and humidity immunity. This can be attributed to the regulation of the gas reaction route at the molecular level. The addition of amphiphilic zinc trifluoromethanesulfonate (Zn(OTf)2) enables the H2O‐poor inner Helmholtz layer to be constructed at the electrode–gel interface, thereby facilitating the direct charge transfer process of NO2 here. The device is then combined with a well‐designed miniaturized low‐power circuit module with signal conditioning, processing and wireless transmission functions, which can be used as wearable electronics to realize early and remote warning of gas leakage. This study demonstrates a promising way to design a self‐powered, sustainable, and flexible gas sensor with high performance and its corresponding wireless sensing system, providing new insight into the all‐in‐one system of gas detection.

Ultra-compact silicon photonics highly dispersive elements for low-latency signal processing.

On-chip optical group-velocity dispersion (GVD) is highly desired for a wide range of signal processing applications, including low-latency and low-power-consumption dispersion compensation of telecommunication data signals. However, present technologies, such as linearly chirped waveguide Bragg gratings (LCWBGs), employ spectral phase accumulation along the frequency spectrum. To achieve the needed specifications in most applications, this strategy requires device lengths that are not compatible with on-chip integration while incurring in relatively long processing latencies. Here, we demonstrate a novel design strategy that utilizes a discretized and bounded spectral phase filtering process to emulate the continuous spectral phase variation of a target GVD line. This leads to a significant reduction of the resulting device length, enabling on-chip integration and ultra-low latencies. In experiments, we show GVD compensation of both NRZ and PAM4 data signals with baud rates up to 24 GBd over a 31.12-km fibre-optic link using a 4.1-mm WBG-based on-chip phase filter in a silicon-on-insulator (SOI) platform, at least 5× shorter compared to an equivalent LCWBG, reducing the processing latency down to ∼ 100 ps. The bandwidth of the mm-long device can be further extended to the THz range by employing a simple and highly efficient phase-only sampling of the grating profile. The proposed solution provides a promising route toward a true on-chip realization of a host of GVD-based all-optical analog signal processing functionalities.

MEDUSA©: A novel Python-based software ecosystem to accelerate brain-computer interface and cognitive neuroscience research

Background and objective: Neurotechnologies have great potential to transform our society in ways that are yet to be uncovered. The rate of development in this field has increased significantly in recent years, but there are still barriers that need to be overcome before bringing neurotechnologies to the general public. One of these barriers is the difficulty of performing experiments that require complex software, such as brain-computer interfaces (BCI) or cognitive neuroscience experiments. Current platforms have limitations in terms of functionality and flexibility to meet the needs of researchers, who often need to implement new experimentation settings. This work was aimed to propose a novel software ecosystem, called MEDUSA©, to overcome these limitations.Methods: We followed strict development practices to optimize MEDUSA© for research in BCI and cognitive neuroscience, making special emphasis in the modularity, flexibility and scalability of our solution. Moreover, it was implemented in Python, an open-source programming language that reduces the development cost by taking advantage from its high-level syntax and large number of community packages.Results: MEDUSA© provides a complete suite of signal processing functions, including several deep learning architectures or connectivity analysis, and ready-to-use BCI and neuroscience experiments, making it one of the most complete solutions nowadays. We also put special effort in providing tools to facilitate the development of custom experiments, which can be easily shared with the community through an app market available in our website to promote reproducibility.Conclusions: MEDUSA© is a novel software ecosystem for modern BCI and neurotechnology experimentation that provides state-of-the-art tools and encourages the participation of the community to make a difference for the progress of these fields. Visit the official website at https://www.medusabci.com/ to know more about this project.

Broadband Terahertz Metal-Wire Signal Processors: A Review

Communication links operating at terahertz frequencies are envisioned to provide a revolutionary enhancement of data transmission. As fundamental building blocks, waveguides play an indispensable role in future terahertz networks, not only transporting data streams with unprecedented data rates, but also serving as a versatile platform for signal processing. Among various terahertz waveguides, metal-wire waveguides have attracted particular attention due to their distinct characteristics, such as structural simplicity, broad operating bandwidths, low transmission losses, and low dispersion, in turn making them promising candidates for signal processing. However, because of the tight confinement of modal energy within the wavelength-scale space, manipulating the propagating terahertz signals in-between the metal-wires is challenging. Here, we report the most recent advances in the realization of signal-processing functionalities within metal-wire waveguides. Based on these state-of-the-art methodologies, broadband signal processors that can function as filters, couplers, temporal integrators, as well as multiplexers, have been obtained. We expect this review to inspire new terahertz metal-wire signal processors with high potential for real-time tunability and reconfigurability.

Enhanced FPGA-Based Controller for Three Phase Shunt Active Power Filter

Abstract In this paper, a three-phase shunt active power filter (SAPF) controller with a fully digital implementation is presented. The main goal of this contribution is to implement a digital direct power control (DDPC) algorithm without phase-locked-loop (PLL) for SAPF. This algorithm is intended for power quality improvement and current harmonic elimination. The controller introduced in this paper is cost-effective, has a fast-dynamic response, and has a simple hardware implementation. In order to comply with the above specifications, a dedicated controller has been conceived and fully implemented within a field-programmable gate array (FPGA) device. This FPGA-based controller integrates the whole signal-processing functions needed to drive the SAPF, as well as an original method for sector identification. The intended controller provides the desired power references to select the optimal switching sequences. The switching orders follow the grid reference to drive the voltage source inverter (VSI), so the SAPF achieves good performances while ensuring balanced overall supply currents, unity power factor, and reduced harmonic load currents. The proposed digital implementation achieves a valuable compromise between fast dynamic response, minimum execution time, and reduced FPGA resources, through a simple hardware design implementation. The entire system is developed and simulated using VHDL and VHDL-AMS languages.

Swallow Neural Network-Empowered High-Speed Brillouin Optical Correlation-Domain Reflectometry: Optimization and Real-Time Operation

In this article, a fiber-optic sensor based on Brillouin optical correlation-domain reflectometry (BOCDR) with a high repetition rate and real-time signal processing function is demonstrated with the assistance of swallow neural networks (NNs) constituted of no more than three hidden layers. In the proposed scheme, the signal processing time for every single Brillouin spectrum is compressed to less than the acquisition period of the spectrum by designing the structure of the NNs, on the basis of the knowledge of the relationship between the implementation time and the preliminary calculation count involved in the NNs. In the experiments with both simulated data and the real-world system, the performances of NNs with different sizes are studied from the perspectives of timing and accuracy. By training NN models with the data acquired from the experiments, real-time dynamic strain measurement is realized with a repetition rate of up to 20 kHz and a dynamic range of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4000 \mu \varepsilon $ </tex-math></inline-formula> . Different from other works regarding machine learning-empowered measurement acceleration in distributed optical fiber sensors with an offline signal processing phase, the method proposed in this article enables consecutive monitoring of the parameters under test.

Review on optical visual sensor technology

视觉传感是人类感知外界、认知世界的主要途径，研究表明人类获取的外界信息大约有80%来自于视觉。作为感知外界信息的“电子眼球”，视觉传感器是消费电子、机器视觉、安防监控、科学探测和军事侦察等领域的核心器件。近年来视觉传感器技术发展迅速，不同类型的传感器从不同维度提供丰富的视觉数据，不断增强人类感知与认知能力，视觉传感器研究工作具有重要的理论与应用需求。本报告以典型光学视觉传感器技术为主线，通过综合国内外文献和相关报道，从CCD图像传感器、CMOS图像传感器、智能视觉传感器以及红外图像传感器等研究方向，梳理论述近年来光学视觉传感器技术的发展现状、前沿动态、热点问题和趋势。;Visual sensing technique is essential for human to perceive and understand the world around them. An electronic eyeball can be melted into outdoor-related visual information, and visual sensors are equipped with such domains like consumer electronics, machine vision, surveillance, and academic researches. Visual sensor technology-based multiple sensors can be used to richer multi-dimension visual data, which can enhance human-related perceptive and cognitive ability. This literature review is focused on the growth of optical visual sensor technology, including such image sensors in relevance to CCD, CMOS, intelligent-visual, and infrared-context. The CMOS image sensor chip is produced in terms of CMOS technology, in which image acquisition unit and signal processing unit can be integrated into the same chip. It can be massproduced to a certain extent. Cost-effective applications can be oriented to such aspects in related to small size, light weight, low cost and low power consumption. With the rapid development of autonomous driving, intelligent transportation, machine vision and other fields, multi-functional and intelligent CMOS image sensors with small size will become the focus of research. The emerging CCD sensor technology and its applications have been facilitating as well. The potentials of CCD image sensor can be applied for such domains in related to remote sensing, astronomy, low light detection. In the future, the multi-spectral TDI CCD architecture based on CCD and CMOS fusion technology will be widely used. Infrared image sensor is configured and set that infrared radiation detection can be converted into physical quantity. The high-performance digital signal processing function can be integrated on the infrared focal plane. The newly infrared image sensor can be focused on larger array, higher resolution, wider spectrums, more flexible sensitivity, multi-band, and system-level chip further.

An Integrated Wearable Sweat Sensing Patch for Passive Continuous Analysis of Stress Biomarkers at Rest

AbstractReal‐time monitoring of mental stress biomarkers in sweat provides the possibility to evaluate mental status in a precise manner. In general, wearable sweat sensors suffer from inconvenient sweat collection, low levels of diagnostic biomarkers in sweat, sophisticated signal processing, and challenges with data visualization. To overcome these challenges, herein an integrated wearable sweat‐sensing patch for continuous analysis of stress biomarkers (cortisol, Mg2+, and pH) at rest is demonstrated. The sweat sensing patch comprised a microfluidic chip, a highly sensitive sensing platform, an on‐site signal processing circuitry (SPCs), and a smartphone installed with a home‐developed display software. The sweat collection at rest is realized using a microfluidic chip without perspiration assistance. A ternary composite electrode is designed to obtain good conductivity, high surface area, and massive reactive sites, thereby yielding excellent electrochemical performances and high sensitivity to trace stress biomarkers. The on‐site SPC has the function of signal transduction, conditioning, processing, and wireless transmission. The detection results can be displayed on a smartphone through the software. This work represents a significant scientific and technological advancement toward indexing mental stress status and can be used as an innovative tool for psychological diagnosis.

Phase retrieval of programmable photonic integrated circuits based on an on-chip fractional-delay reference path

Programmable photonic integrated circuits (PICs), offering diverse signal processing functions within a single chip, are promising solutions for applications ranging from optical communications to artificial intelligence. While the scale and complexity of programmable PICs are increasing, their characterization, and thus calibration, becomes increasingly challenging. Here we demonstrate a phase retrieval method for programmable PICs using an on-chip fractional-delay reference path. The impulse response of the chip can be uniquely and precisely identified from only the insertion loss using a standard complex Fourier transform. We demonstrate our approach experimentally with a four-tap finite-impulse-response chip. The results match well with expectations and verify our approach as effective for individually determining the taps’ weights without the need for additional ports or photodiodes.

The concept of PICaboo: from individual building blocks to complex photonic integrated circuits for future access and metro networks

The immense growth of data traffic that traverses modern networks, calls for immediate solutions to tackle the challenges that arise in terms of speed, capacity, cost and energy efficiency. This manuscript outlines the key technological aspects of the PICaboo project, that aims to develop novel building blocks and photonic integrated circuits for the next generation of optical metro and access networks enhanced with optical signal processing functionalities exploiting the generic foundry model approach.

Compact and efficient radio frequency digital feedback control system for accelerator applications

The digital feedback (DFB) setup employed in a low-level radio frequency (LLRF) control system is crucial to ensure RF field stability in accelerating cavities, thus guaranteeing successful operation. To this end, a novel in-house and multi-purpose prototype DFB setup was developed for multiple applications at the Japan Proton Accelerator Research Complex (J-PARC). Being efficient, low-cost, and compact is key to achieving a cost-effective system that fulfills the performance specifications. It also reduces the production and maintenance costs of future DFB setups. A field-programmable gate array (FPGA)-based design with a digital signal processing (DSP) function uses an analog in-phase/quadrature-phase (I/Q) demodulator for RF-to-baseband signal conversion and an I/Q modulator to generate RF power. This arrangement compensates for RF phase fluctuations and amplitude modulations by employing a proportional and integral (PI) feedback controller. In addition, systematic errors are minimized by applying a hardware-error-compensation process. The system was utilized to conduct high-power tests on the interdigital H-mode drift-tube linac (IH-DTL) cavity of a muon linac for short RF pulses. The setup was also tested on a buncher cavity (Buncher-2) in the J-PARC linac, achieving efficient performance for longer RF pulses. The stability of the RF accelerating field in the IH-DTL was achieved at ±0.25% peak-to-peak (pp) in amplitude and ±0.36 degree pp in phase. For the Buncher-2, the amplitude stability of ±0.18% pp and phase stability of ±0.13 degree pp were obtained. Therefore, this DFB setup can be used to conduct high-power tests of RF cavities and klystrons. This study discusses the design aspects of a cost-effective DFB system and reports high-power measurements.

Digital filtering dissemination for optimizing impedance cytometry signal quality and counting accuracy.

Improving biosensor performance which utilize impedance cytometry is a highly interested research topic for many clinical and diagnostic settings. During development, a sensor's design and external factors are rigorously optimized, but improvements in signal quality and interpretation are usually still necessary to produce a sensitive and accurate product. A common solution involves digital signal processing after sample analysis, but these methods frequently fall short in providing meaningful signal outcome changes. This shortcoming may arise from a lack of investigative research into selecting and using signal processing functions, as many choices in current sensors are based on either theoretical results or estimated hypotheses. While a ubiquitous condition set is improbable across diverse impedance cytometry designs, there lies a need for a streamlined and rapid analytical method for discovering those conditions for unique sensors. Herein, we present a comprehensive dissemination of digital filtering parameters applied on experimental impedance cytometry data for determining the limits of signal processing on signal quality improvements. Various filter orders, cutoff frequencies, and filter types are applied after data collection for highest achievable noise reduction. After designing and fabricating a microfluidic impedance cytometer, 9µm polystyrene particles were measured under flow and signal quality improved by6.09dB when implementing digital filtering. This approached was then translated to isolated human neutrophils, where similarly, signal quality improved by7.50dB compared to its unfiltered original data. By sweeping all filtering conditions and devising a system to evaluate filtering performance both by signal quality and object counting accuracy, this may serve as a framework for future systems to determine their appropriately optimized filtering configuration.