Digital Signal Processing Research Articles

Determining the optimal sampling interval for 3D morphology measurements of different-sized natural rock joints

Efficiently studying the scale effect of surface roughness and peak shear strength of natural rock joints, especially unfilled and well-matched ones, requires an optimal sampling interval to realize cost-effective three-dimensional morphology measurements for different-sized natural rock joints with advanced non-contact optical devices. However, rationally determining such an optimal sampling interval remains controversial. To this end, inspired by digital signal processing, the optimal sampling interval is creatively determined by Shannon's sampling theorem using the Fourier series' optimum order. An empirical formula relating the joint size to the optimum order is correspondingly developed. The proposed empirical formula was found to work well under conditions of high normal stress, where the relative errors for the surface roughness and peak shear strength of series-sized natural rock joints were mostly less than 10% and 5%, respectively, but should be used cautiously under conditions of low normal stress. Furthermore, different from previous perceptions, a higher joint roughness level was discovered to not necessarily imply the need for a smaller optimal sampling interval, and conversely. The proposed empirical formula can facilitate the determination of the optimal sampling interval for measuring different-sized natural rock joints' surface morphologies in engineering practice.

THE NOVEL CFRG -BASED COMPLEX FUZZY TRANSFER LEARNING SYSTEM

Today, the rapid development of the internet has led to a data explosion; the complex fuzzy transfer learning (CFTL) model has received increasing attention from the academic community due to its various real-world applications, such as solar activity, digital signal processing, time series forecasting, etc. CFTL combines Transfer learning and Complex Fuzzy Logic in a framework to solve the problem of learning tasks with no prior direct contextual knowledge, which is stored, retrieved, and organized in the data structure. Data structures play an important role in computational intelligence because they are key performance indicators for systems or models. Therefore, to improve the performance of the previous CFTL, this paper investigates a novel complex fuzzy decision tree (CFDT) structure to represent the complex fuzzy rules and provides a transfer learning model for a complex fuzzy inference system. In contrast with prior axis-parallel decision trees in which only a single feature or variable is considered at each node, the node of the proposed decision tree structures includes complex fuzzy inference rules that contain multiple elements. Multiple features for each node help minimize the size. To prove the efficiency of the proposed framework, we carry out extension experiments on numerous instances (datasets). Experimental results demonstrate/exhibit that our offered performs better than the prior framework regarding accuracy and the size of the produced trees.

Energy and self-adaption in a memristive map neuron

Both capacitor and charge-controlled memristor (CCM) can regulate the inner energy levels during the release and accumulation of charges in these electronic components. Combination of inductive and capacitive components is crucial to build an oscillatory circuit, and incorporation of a nonlinear resistor is helpful to support nonlinear oscillation under continuous energy exchange between magnetic field and electric field. Relation between physical variables in neural circuits can be described by some equivalent nonlinear oscillators by applying scale transformation on the variables and parameters for the neural circuit, and the energy function becomes available from theoretical approach. In this work, a simple neural circuit coupled with a CCM is designed to obtain a memristive neuron model, and then linear transformation is applied to the sampled variables involved with time scale for time step, a new memristive map is obtained to discuss its energy characteristic and self-controllability under energy flow. The result provides guidance to measure the reliability of maps, and the new derived maps with reliable physical evidences can be further used in digital signal processing.

Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This article provides an overview of types of servomotors and their basic principles and control methods. Principles such as digital signal processing, feedback control principle, field-oriented control, and integration with Industry 4.0 are discussed. Based on these control principles, the article presents popular control methods: PWM control, current control, two-loop control, fuzzy-logic control, and programmable control. The article concludes with a comparison of the presented methods on several criteria, and as an example, it includes the results of modeling a servomotor using the fuzzy-logic control method.

All-Fiber Low-Modal-Crosstalk Demultiplexers for DSP-Free IM/DD LP-Mode MDM Transmission

Weakly coupled mode-division multiplexing (MDM) techniques supporting intensity modulation and direct detection (IM/DD) transmission are promising methods of enhancing the capacity of short-reach scenarios in which low-modal-crosstalk-mode demultiplexers for degenerate linear polarized (LP) modes are highly desired. In this paper, we review two degenerate-mode reception schemes. Firstly, a low-modal-crosstalk orthogonal combined reception method for degenerate modes is proposed based on all-fiber mode-selective couplers, in which signals in both degenerate modes are demultiplexed into the LP01 mode of single-mode fibers and then are multiplexed into the mutually orthogonal LP01 and LP11 modes of a two-mode fiber (TMF) for simultaneous detection. Secondly, a novel degenerate-mode-selective coupler consisting of an input few-mode fiber and an output TMF is proposed, which could demultiplex degenerate LP modes without any digital signal processing (DSP). Both demultiplexers are achieved based on the taper and polish process. The fabricated devices are characterized and compared. The results show that the proposed schemes can pave the way to the practical implementation of DSP-free IM/DD LP-mode MDM transmission systems.

Radar near-field sensing using metasurface for biomedical applications

Metasurfaces, promising technology exemplified by their precise manipulation of incident wave properties and exquisite control over electromagnetic field propagation, offer unparalleled benefits when integrated into radar systems, providing higher resolution and increased sensitivity. Here, we introduce a metasurface-enhanced millimeter-wave radar system for advanced near-field bio-sensing, underscoring its adaptability to the skin-device interface, and heightened diagnostic precision in non-invasive healthcare monitoring. The low-profile planar metasurface, featuring a phase-synthesized array for near-field impedance matching, integrates with radar antennas to concentrate absorbed power density within the skin medium while simultaneously improving the received power level, thereby enhancing sensor signal-to-noise ratio. Measurement verification employs a phantom with material properties resembling human skin within the radar frequency range of 58 to 63 GHz. Results demonstrate a notable increase of over 11 dB in near-field Poynting power density within the phantom model, while radar signal processing analysis indicates a commensurate improvement in signal-to-noise ratio, thus facilitating enhanced sensing in biomedical applications.

Power-aware high-capacity elastic optical networks

The power consumption of telecommunication equipment has been identified as a relevant contributor to global energy consumption. In fact, new-generation optical transponders employ power-intensive electronic application-specific integrated circuits (ASICs) for digital signal processing (DSP). DSP design has traditionally prioritized meeting transmission requirements over power consumption optimization. In general, the evolutions of transmission techniques and network design have always been mainly driven by traffic increase; in this context, in order to operate network resources more efficiently, margin reduction has been investigated in the past few years. Indeed, traditionally, high physical layer margins are used to ensure reliability over an extended period, resulting in overprovisioning the optical connections for both physical layer conditions and capacity. On the other hand, super-channels have emerged as a suitable solution for accommodating the continuous traffic growth. However, power consumption has not been deeply considered in the optimization of super-channel transmission. This paper first investigates the power efficiency of super-channels operated with designed and reduced margins. Low-margin operation is enabled by adapting sub-carrier spacing and filter bandwidth. Power-aware super-channel optimization is then experimentally demonstrated leveraging a 600 Gbit/s transponder in the SDN-controlled elastic optical network (EON). The results have identified a trade-off between power consumption and spectrum efficiency. Furthermore, the ongoing bandwidth demand has motivated the investigation of multi-band (MB) transmission for scaling the capacity of the existing infrastructures. However, novel networking devices (e.g., optical amplifiers operating beyond the C- and L-bands) will affect the overall power consumption. In this context, experimental power analysis of a thulium doped fiber amplifier (TDFA) is performed based on the traffic load and corresponding configuration. The results show that TDFA power consumption varies with configuration and increases with output power.

RF direct sampling and processing electronics for SHINE cavity BPM system

Cavity BPMs are crucial for achieving submicron beam alignment in X-ray Free-Electron Lasers (XFEL), particularly in undulator sections. These monitors typically generate RF signals in the S, C, or X band regions. Due to the limitations of analog-to-digital converter's (ADC) bandwidth and sampling rates, and digital signal processing capabilities, heterodyne and homodyne receivers are often employed to down-convert the RF signal to an intermediate frequency (IF) or baseband (Zero IF) respectively before digital sampling. The digitized signal is then processed by Field Programmable Gate Array (FPGA) to get the beam position and phase information. An RF direct-sampling beam signal processor has been developed using ADCs with a bandwidth of 9 GHz and a sampling rate of 2.6 GSPS, and a powerful system-on-chip FPGA. In addition, a prototype RF module without complex down conversion devices has been designed for the SHINE (Shanghai High Repetition Rate XFEL and Extreme Light Facility) cavity BPM. The processor and the RF module make a novel RF direct sampling and processing cavity BPM electronics for SHINE. This is the first attempt to use direct sampling electronics in the C band cavity BPM system. The analog signal processing chain is greatly simplified compared to the down-conversion structure. The performance of this electronics has been analyzed and evaluated in laboratory. The amplitude relative error is 2.0 × 10-4, surpassing the required accuracy of 1 × 10-3 for cavity BPM systems. The phase error is 14 femtoseconds (fs), which also meets the requirements for an RF Beam Arrival Time Monitor (BAM) system. Additionally, the paper introduces the cavity BPM signal processing algorithms and their implementation in FPGA. The processor can deliver pulse-to-pulse beam position measurement above 1 MHz. The RF direct-sampling electronics represents significant advancements in cavity BPM system, large-scale application can be carried out in accelerator facilities like SHINE.

Классификация сигналов ЭКГ на основе цифровой обработки сигналов, технического выбора функций и радиочастотного классификатора

Determining the optimal integration between features and classifiers has a significant effect on the performance of automatic heartbeat diagnostic systems. This importance stands out when dealing with critical applications that contain limited resources devices and require accurate and fast heartbeat classifiers to help the doctor make an accurate and quick diagnosis of heart diseases. Aiming at this task, this paper introduces a novel approach for choosing the optimal features of the ECG signal to be used with the Random Forest (RF) classifier following the inter-patient method for ECG signals division and obeying the instructions of the "Association for the Advancement of Medical Instrumentation (AAMI)." The features were chosen based on the concept of "Mutual Information Ranking (MIR)." The presented framework is comprehensive in terms of performing all the necessary processes efficiently, starting from ECG digital signal processing, segmentation, feature extraction, feature selection, and ending with ECG classification. The results of the experiments demonstrate that features corresponding to the normalized QRS width and the normalized RR intervals are the most influential features in the heartbeat classification. All tests were conducted using real ECG signals taken from the "MIT-BIH" Arrhythmia Database (MIT-BIH-ARR-DB). The suggested scheme attained the following F1-scores: 91.02%, 73.17%, and 98.04% in the classification of the Ventricular Ectopic Beats (V or VEB), Supraventricular Ectopic Beats (S or SVEB), and Normal Beats (N or NB), respectively. The overall accuracy was 96.26%. Despite its relative simplicity and reliance on few features, the proposed approach outperforms most of the reported state-of-the-art.

Novel Spectral Approaches in Mathematical Bioacoustics Based on Real Time Analysis and Modern Computational Mathematical Techniques Using Digital Signal Processing and Analog Signal Processing Hardware (Review Lecture)

This review publication is an expanded version of the 2015 lecture at the III Moscow Seminar on Mathematical Bioacoustics and Analog Signal Processing in Physiology. Unlike the original 2015 version, this version includes developments by E.D. Adamovich and F.K. Orekhov, as well as a number of graphic materials of historical value. The work proposes new principles or approaches for multifactori/multimodal analysis of various bioacoustic signals based on N-dimension complex spectral analysis of different (bio) physical variables - “bioacoustic fingerprinting” and “bioacoustic footprinting”. Hadware-based technical examples of possible uses of this approache are given for the breef annotation in the text of this lecture.

SC and OFDM hybrid coherent optical transmission scheme based on 1-bit bandpass delta-sigma modulation.

High-order quadrature amplitude modulation (QAM) can effectively improve the capacity and spectral efficiency of coherent optical transmission systems. However, as the modulation order increases, the signal becomes less tolerant to noise and nonlinear effects during transmission, and the implementation cost also increases. We propose a single carrier (SC) and orthogonal frequency division multiplexing (OFDM) hybrid coherent optical transmission scheme based on a 1-bit bandpass (BP) delta-sigma modulation (DSM). The driving I-channel and Q-channel signals for the optical in-phase/quadrature (I/Q) modulator carry SC-modulated and OFDM-modulated transmitter data, respectively. Optical quadrature-phase-shift-keying (QPSK) modulation is realized by the 1-bit DSM quantizer and I/Q modulator, which can effectively suppress quantization noise and reduce the complexity of digital signal processing (DSP) and the performance requirements of optoelectronic devices. In addition, the hybrid transmission of SC and OFDM can balance the advantages of both to meet the variable channel conditions and complex application scenarios. High-fidelity transmission of SC 512QAM and OFDM 512QAM hybrid signals, in the form of a 60 Gbaud optical QPSK signal, over 60 km single-mode fiber-28 (SMF-28) is verified by offline experiments, and the bit error rates (BERs) of both SC 512QAM and OFDM 512QAM are below the hard-decision forward-error correction (HD-FEC) threshold of 3.8e-3.

Optimized pilot structure for PS-PDM ultrahigh-order QAM coherent optical transmission

We proposed and experimentally demonstrated a general pilot structure for probabilistic shaped (PS)-polarization division multiplexing (PDM) M-ary quadrature amplitude modulation (MQAM) coherent optical transmission, where a portion of PS-MQAM symbols is exploited as the pilot symbols with the same information entropy as the transmitted signal. The pilot symbols are simultaneously used in the entire digital signal processing (DSP) modules for polarization de-multiplexing, frequency offset estimation, carrier phase recovery, nonlinear equalization, and linear equalization. Compared to the conventional quadrature phase shift keying (QPSK) pilot structure, the proposed MQAM pilot structure can yield the nonlinear properties of the overall signal so that nonlinear equalization can effectively improve the performance of the normalized generalized mutual information. The remarkable performance has been achieved at the shaping parameters of 3.25 and 4.35 for 1024QAM and 4096QAM signals based on the proposed pilot scheme, which corresponds to the raw spectral efficiency of 16.190 and 20.381 bit/s/Hz, respectively. The pilot ratio is optimized to 5% for higher achievable information rates (AIRs).

Operation of a Ramsey-CPT microcell atomic clock with driving current-based power modulation of a VCSEL

We report on the operation of a coherent population trapping (CPT) microcell atomic clock using a pulsed Ramsey-like interrogation. The Ramsey-CPT sequence, defined by two-step optical pulses separated by a free-evolution dark time, is produced by switching on and off the output power of a low-power vertical-cavity surface-emitting laser, through direct modulation of its driving current. High-contrast and narrow Ramsey-CPT fringes are detected without the use of any external optical modulator stage. We demonstrate closed-loop operation of the clock based on high-speed digital signal processing implemented in a field programmable gate array board. The clock's short-term fractional frequency stability is 1.3 × 10−10τ−1/2 until 2000 s. A power light-shift coefficient of 8 × 10−11/μW, in relative value, is obtained for a dark time of 150 μs. This value is about ten times lower than in the continuous regime. These results show the feasibility of fully integrated atomic clocks based on Ramsey spectroscopy, which could provide enhanced long-term stability.

Research on Image Processing Resource Reconstruction Based on Load Balancing Strategy

With the development of intelligent vehicles, the vehicle image processing system has put forward increasing demand for computing resource utilization efficiency and real-time processing. However, the traditional information processing method that binds software and hardware severely restricts the efficient use of image processing resources. In order to solve this problem, this paper proposes a resource reconstruction scheme based on a load balancing strategy, which can realize unified management and dynamic allocation of image processing resources by establishing a system resource view. Then, this paper builds a physical verification platform and constructs a comparative verification experiment to verify the effectiveness of the resource reconstruction scheme. Experimental results prove that this resource reconstruction scheme can effectively improve the resource utilization efficiency of multi-core digital signal processing (DSP), realize software-defined hardware functions, and optimize the real-time performance of parallel processing.

Graphene nanomechanical vibrations measured with a phase-coherent software-defined radio

Software-defined radios (SDRs) are radio frequency transceivers designed to facilitate digital signal processing through the use of vast libraries of open-source software. Here, we assemble a simple data acquisition system whose architecture, based on SDR, allows us to develop a comprehensive suite of tools to study the vibrations of a few-layer graphene nanomechanical resonator. Namely, we measure the cross-spectrum of vibrations in the frequency domain, we measure their energy decay rate in the time domain, we perform vector measurements of their in-phase and quadrature components, and we control their phase using a time-dependent strain field –all with a single measurement platform. Our approach allows us to tailor our experiments at will and gives us control over every stage of data processing. Overall, our versatile system enables measuring a wide range of nanomechanical properties of graphene by customizing the signal acquisition and replacing some analog electrical circuits, such as filters, mixers, and demodulators, by blocks of code.

A convenient acoustic measurement of femtosecond filamentation based on a cell phone

The acoustic diagnostic method has been widely used in diagnosing femtosecond filamentation. In this work, acoustic measurements of femtosecond laser filamentation and weakly air-ionized region are conducted using a readily available portable device - a cell phone. The signal is extracted by employing digital signal processing method of Fourier transformation filtering. The results demonstrate that the method can be used for effective measurements even in noisy environments. This greatly enhances the accuracy and portability of the acoustic method, providing a practical approach for improving acoustic diagnostics.

Implementation of FIR Filters through Inner product Units and Parallel Accumulations

Finite Impulse Response (FIR) filters are pivotal in digital signal processing, finding applications in diverse fields like audio processing, telecommunications, and biomedical signal analysis. This work presents an enhanced implementation methodology for FIR filters utilizing inner product computation and parallel accumulations. In the existing, FIR filters are typically implemented using convolution techniques, basic adders, and multipliers, which involve sequential processing and intensive computational resources. This method often leads to latency issues and limits real-time applications. Moreover, traditional implementations suffer from inefficiencies in utilizing hardware resources optimally, leading to suboptimal performance. The proposed methodology overcomes these limitations by leveraging inner product computations and parallel accumulation techniques. By exploiting inherent parallelism in the filtering process, the proposed method significantly reduces latency and enhances throughput.

Implementation of Systolic Multiplier Using Hybrid Multiplexer Dependent Adder

Multipliers are basic building blocks in various integrated circuits like microprocessors, micro controllers, and ALUs. The existing multipliers suffer from high power consumption and inefficient use of hardware resources. They often rely on traditional adder structures that are not tailored for specific operations, leading to suboptimal performance. Additionally, their fixed architectures limit adaptability and scalability in different applications. So, the proposed approach offers enhanced computational efficiency and reduced power consumption compared to conventional multiplier designs. By integrating multiplexer-dependent adders into the systolic array, the proposed method optimizes resource utilization and delivers improved performance for various arithmetic operations. This integration allows for dynamic selection of adder types based on the specific multiplication operation, significantly reducing power consumption and latency. By adapting the hardware resources to computational needs, the method achieves higher efficiency and flexibility, making it suitable for a wide range of applications in digital signal processing and data processing systems.

Magnetic resonance imaging at low signal-to-noise ratio, electromagnetic interferences and hardware imperfections

The problems of magnetic resonance (MR) scanning at low signal-to-noise ratio, electromagnetic interference (EMI) and equipment imperfections are considered. Attention is paid to pulsed interference, as well as interference represented by continuous radiation, the frequency and amplitude of which vary chaotically over time. Manifestations of hardware and software imperfections leading to distortions of MR images were noted. These include, in particular, failures in digital signal processing (DSP) and direct current (DC) offset correction algorithms. These imperfections can be caused by various reasons - software errors, poor shielding, aging equipment, etc. Recently, articles have appeared that recommend detecting EMI based on the analysis of electromagnetic coupling between sources and spatially distributed receiving coils connected to a multi-channel receiver, and based on this information, eliminating EMI from MRI data. If such resources are not available when conducting MRI studies, then simple procedures described in this paper can be used to minimize or suppress interference. They involve planning the research time taking into account the dynamics of the interference environment, setting an extremely narrow receiver bandwidth, as well as editing k-space points distorted by interference and hardware factors. The issues of optimizing scanning parameters are considered, in particular those related to setting the matrix size and sampling frequency, as well as practical aspects of data processing, in particular the use of apodization in k-space. The methods described in the article were used for 23Na MRI of the human head on a clinical 0.5 T scanner, the adaptation of which for detecting sodium signals was reduced only to modification of the proprietary receiving coil. It has been shown that with standard processing of MR data, images are uninformative. But if the k-space data is edited before the Fourier transform, then the information content of sodium images becomes comparable to proton ones if scans are performed with the same spatial resolution and similar tissue contrast.

Digital Signal Processing Oriented Electronic Communication Engineering Applications and Practices

This paper first describes the applications of digital signal processors in software radio, speech compression coding, modems and GPS systems, demonstrating the versatility of digital signal processors in practical communication systems. Next, digital signal processing oriented electronic communication practices are presented in the system design section to design high performance communication systems for specific communication needs and environmental conditions. The digital signal processing platform used in the platform architecture is optimized for signal processing and data transmission. The BER is 0.008% when the signal-to-noise ratio is -10 dB. The time complexity of digital signal processing is 7.2 ms when the number of communication nodes is 1000. It shows that digital signal processing oriented electronic communication engineering is important for improving the performance, reliability and efficiency of communication systems.