Optimal Signal Processing Research Articles

Direct 3-D Sparse Imaging Using Non-Uniform Samples Without Data Interpolation

As an emerging technique, sparse imaging from three-dimensional (3-D) and non-uniform samples provides an attractive approach to obtain high resolution 3-D images along with great convenience in data acquisition, especially in the case of targets consisting of strong isolated scatterers. Although data interpolation in k-space and fast Fourier transform have been employed in the existing 3-D sparse imaging methods to reduce the computational complexity, the data-gridding errors induced by local interpolation may usually result in poor imaging performance. In this paper, we directly regard the imaging problem as a joint sparse reconstruction problem from non-uniform data without interpolation in 3-D space. Combining dictionary reduction and Gauss iterative method with the optimized signal processing scheme, a sparse imaging algorithm is proposed to address the difficulty of large-scale computation involved in direct 3-D sparse reconstruction. Benefited from the optimized signal processing scheme and the avoidance of data interpolation, the direct 3-D sparse imaging (DTDSI) method proposed in this paper is of low computation scale and high imaging performance. Experiments of electromagnetic simulation data demonstrate the DTDSI method outperforms baseline methods in terms of resolving ability, lower side-lobes and higher accuracy.

The Object Detection Efficiency in Synthetic Aperture Radar Systems

The main purpose of this paper is to develop the method of characteristic functions for calculating the detection characteristics in the case of the object surrounded by rough surfaces. This method is to be implemented in synthetic aperture radar (SAR) systems using optimal resolution algorithms. By applying the specified technique, the expressions have been obtained for the false alarm and correct detection probabilities. In order to illustrate the effective application of the introduced approach in the case of the generic SAR system, the results are presented of the calculation of the detection characteristics of the signal from the extended object surrounded by a rough surface. It is shown that the analysis allows us to substantiate the structure of the SAR signal processing channel and to obtain the improved relations for the radio observation characteristics in this case. The efficiency of the optimal signal processing in SAR systems can also be determined without the approximate calculations involved.

SciFi detector and associated method for real-time determination of profile and output factor for small fields in stereotactic radiotherapy.

PurposeFor determining small‐field profile and output factor during stereotactic radiotherapy quality assurance (QA) procedures, we propose a novel system based on the scintillating fiber (SciFi) detector with output image acquisition and processing to allow real‐time monitoring of profile and output factor.Materials and methodsThe employed detector is a SciFi detector made of tissue‐equivalent scintillating plastic fibers arranged in 6‐layer fiber ribbons with a fiber pitch of 275 μm in each layer. The scintillating signal at the detector output is acquired by a sCMOS (scientific complementary metal–oxide–semiconductor) camera and represents the projected field profile along the fibers axis. An iterative reconstruction method of the field from its projected profile based on a priori knowledge of some features of the radiation field defined by the stereotactic cones is suggested. The detector with implemented data processing has been tested in clinical conditions, for determining beam profiles and output factors, using cone collimators of different sizes from 4 to 15 mm diameter. The detector under test was placed at 1.4 cm depth and 98.6 cm source to surface distance (SSD) in a water‐equivalent phantom and irradiated by a 6 MV photon beam.ResultsThe reconstructed field profiles obtained from the detector are coherent with data from EBT3 radiochromic films, with differences within ±0.32 mm for both the FWHM and the penumbra region. For real‐time determination of the field output factor, the measured data are also in good agreement with data independently determined by the French Institute for Radiological Protection and Nuclear Safety (IRSN) based on radiochromic films and thermoluminescent 1 × 1 mm2 micro‐cubes dosimeters (TLD). The differences are within ±1.6% for all the tested cone sizes.ConclusionsWe propose and have tested a SciFi plastic scintillating detector with an optimized signal processing method to characterize small fields defined by cone collimators. It allows the determination of key field parameters such as full width at half maximum (FWHM) and field output factors. The results are consistent with those independently measured using TLD and radiochromic films. As the SciFi detector does not require a correction factor, it is in line with the International Atomic Energy Agency (IAEA) and the American Association of Physicists in Medicine (AAPM) TRS‐483 recommendations, and can be suitable for online QA of small radiation fields used in photon beam radiotherapy, and is compatible with MRI‐LINAC.

Communication Under Channel Uncertainty: An Algorithmic Perspective and Effective Construction

The availability and quality of channel state information heavily influences the performance of wireless communication systems. For perfect channel knowledge, optimal signal processing and coding schemes have been well studied and often closed-form solutions are known. On the other hand, the case of imperfect channel information is less understood and closed-form characterizations of optimal schemes remain unknown in many cases. This paper approaches this question from a fundamental, algorithmic point of view by studying whether or not such optimal schemes can be constructed algorithmically in principle (without putting any constraints on the computational complexity of such algorithms). To this end, the concepts of compound channels and averaged channels are considered as models for channel uncertainty and block fading and it is shown that, although the compound channel and averaged channel themselves are computable channels, the corresponding capacities are not computable in general, i.e., there exists no algorithm (or Turing machine) that takes the channel as an input and computes the corresponding capacity. As an implication of this, it is then shown that for such compound channels, there are no effectively constructible optimal (i.e., capacity-achieving) signal processing and coding schemes possible. This is particularly noteworthy as such schemes must exist (since the capacity is known), but they cannot be effectively, i.e., algorithmically, constructed. Thus, there is a crucial difference between the existence of optimal schemes and their algorithmic constructability. In addition, it is shown that there is no search algorithm that can find the maximal number of messages that can be reliably transmitted for a fixed blocklength. Finally, the case of partial channel knowledge is studied in which either the transmitter or the receiver have perfect channel knowledge while the other part remains uncertain. It is shown that also in the cases of an informed encoder and informed decoder, the capacity remains non-computable in general and, accordingly, optimal signal processing and coding schemes are not effectively constructible.

Perceptually optimized signal processing for vibro-acoustical music reproduction

Perceptually optimized signal processing for vibro-acoustical music reproduction

Research and development of hierarchical models of automated control systems for the parameters of the radio-line of the cognitive radio system

The paper considers a five-level model of a cognitive radio communication system. It was revealed that the value of the influence of natural factors and the effects of the enemy is comparable, but several times less than the state of the radio communication system. The observer’s device and the regulator are important for the effective transmission of information and the controlled process and the internal state of the information transmission system are less important. The goal of reducing the number of errors in the transmission of information and increasing the speed of information transmission are important for the effective transmission of information, in comparison with a reduction in the computational load on the formation of signal-code structures and a decrease energy used for transmission. The highest efficiency of the radio system can be achieved through the use of optimal signal processing algorithms, and high power of the transmitted signal. High speed of information transmission will not give a tangible effect when transmitting information in difficult conditions without the necessary power of the radio link and signal processing algorithms.

Modernized Solar Radio Spectrograph in the L Band Based on Software Defined Radio

The paper presents the concept, implementation, and test operation of a modernized solar radio spectrograph for an investigation of the solar emission and solar bursts in radio frequency bands. Besides having a strong diagnostic significance for studying the flare energy release, the solar radio bursts can also cause strong interference for radio communication and navigation systems. The current spectrograph for the Ondrejov observatory (Astronomical Institute of Czech Academy of Sciences) was modernized by using a direct-conversion receiver connected to a field-programmable gate array (FPGA) for the fast Fourier transform (FFT) spectrum estimation and put into the test operation. The higher time and frequency resolution and lower noise in comparison with the existing analog instrument were reached by the implementation of the latest optimal signal processing methods. To reduce the costs for such modernization, the operating frequency range was divided into four sub-bands of bandwidth 250 MHz, which brings another benefit of greater scalability. The first observations obtained by the new spectrograph and their comparison with the analog device are presented in the paper with future steps to put the spectrograph into the regular operation.

METHODS FOR IMPLEMENTING NEURAL NETWORK HYDROACOUSTICS ALGORITHMS BASED ON HETEROGENEOUS HARDWARE PLATFORM GRIFON

Recently, there has been an increase of interest in creating new neural network hydroacoustics algorithms, for example, test sites in the Arctic are being created to evaluate the effectiveness of target detection and to ensure the safety of the Canadian North. The open architecture allows you to adapt hardware to new threats or economic interests. Not only the equipment of radiation and reception of hydroacoustic systems is improved, but also their processing. The article discusses the ways of improvement and the principles of building specialized computers based on the GRIFON hardware platform, providing control and signal processing in mobile and stationary sonar systems. We consider an example of creating a complex that demonstrates the capabilities of the equipment and the prospects for creating calculators with high parameters and minimal mass‑dimensional characteristics. Described in detail the structure and principles of the mathematical software of specialized computer. Comparative characteristics of the proposed algorithms that can be used to optimize signal processing paths and the volume of digital equipment are given.

Optimal designs of analogue and digital fractional order filters for signal processing applications

Our initial research work was focussed on employing metaheuristic optimization techniques to design optimal digital signal processing (DSP) systems such as the full band, conventional infinite impulse response differentiators and integrators meeting the accurate magnitude responses with a smaller average group delay. Since, integer order systems are a tight subset of the fractional order (FO) systems the research has been extended towards the optimal design of FO differentiators and integrators in the discrete domain with improved frequency response performances. Specific emphasis was laid on the feasibility of the designed FO differentiators in controlling a double-integrator plant. Analogue Butterworth filter with fractional stepping in the transition band has also been realized using an optimal integer-order rational transfer function. In future, we intend to design and implement generalized fractional-order filters on FPGA/DSP kit and FPAAs.

XSG-based HLS flow for optimized signal processing designs for FPGAs

This paper proposes an XSG(Xilinx System Generator) based HLS (High level synthesis) flow for FPGAs. The tool includes an operation classification process and a formal clustering technique for an optimized allocation phase. During the binding step, a new target based resource sharing strategy is proposed. We demonstrate the effectiveness of the proposed tool against the direct implementation using both Xilinx System Generator, Vivado HLS, Legup and (Ronak and Fahmy, 2016 [1]) on several benchmarks from the signal processing domain. The results show significant improvements. The power consumption enhancement reached 79% in comparison with the direct implementation, 50% in comparison with the Vivado HLS implementation and 70% in comparison with (Ronak and Fahmy, 2016 [1]). The area improvement attained 85% in comparison with the direct implementation, 90% in comparison with the Vivado HLS implementation, 88% in comparison with Legup and 82% in comparison with (Ronak and Fahmy, 2016 [1]).

PERSPECTIVES OF DIGITAL PROCESSING FACILITIES CONSTRUCTION FOR SYSTEMS OF OVER-THE-HORIZON RADAR ON BASIS OF GRIFON HARDWARE PLATFORM

The ways of improving and the principles of constructing specialized computers that provide control and signal processing in mobile and stationary over‑the‑horizon radar systems are discussed in the article. A brief review of the history of the development of over‑the‑horizon radar is presented. Potential capabilities of the equipment are considered, demonstrating the prospects of creating specialized computers based on the Gryphon hardware platform with high parameters and minimal mass‑size characteristics. The structure and principles of constructing the mathematical support of specialized computers are described in details. Algorithms are proposed that provide an increase in the efficiency of signal processing, taking into account the structure of electromagnetic fields formed during the propagation of waves in the ionosphere. The comparative characteristics of the proposed algorithms that can be used to optimize signal processing and digital equipment volumes are given.

Optimal signal processing algorithm at the background of non-Gaussian flicker noise

The problem of receiving and processing ultra-low-power signals of information transmission systems is being solved. High requirements for energy efficiency on the one hand and a low information transfer rate allows the use of signals with a small spectrum width, including flicker noise spectral regions. A non-Gaussian flicker noise model is used based on a stochastic differential equation with a nonlinear drift coefficient. An optimal signal processing algorithm is being developed against the background of the sum of flicker noise and thermal noise based on an estimated-correlation-compensation approach. The analysis of the effectiveness of optimal signal processing against a background of non-Gaussian flicker noise and thermal noise is carried out.

Analysis of confidentiality of information transfer in DSSS systems in conditions of limited systems of used signal constructions

Information security in telecommunications can be provided at the physical level of telecommunication systems by means of energy and structural secrecy of information transfer. Spread-spectrum telecommunications, in particular the DSSS (Direct Sequence Spread Spectrum) technique, are the most suitable for the implementation of such approach to information security. Ensuring the necessary level of structural secrecy of information transfer using DSSS technique is that this technique uses systems of signal constructions with a sufficiently large number of signals in the system. There are requirements to correlation properties of each such signal construction, because in accordance with the Wiener-Khinchin theorem they determine the spectral characteristics of signals in a telecommunication system and, as a result, the structural spectral and energy secrecy of information transfer. The problem boils down to the fact that the systematic deterministic methods for synthesizing systems of signal constructions with a low peak sidelobe level of the autocorrelation function for the case of an arbitrary length of signal constructions and the number of ones in the system of signals are unknown, and the complexity of this problem is associated with an algorithmic undecidability of arbitrary algebraic Diophantine equations. The confidentiality of information transfer at the physical level of DSSS telecommunication systems while using some known systems of signal constructions with a low peak sidelobe level of the autocorrelation function and in the case of attacks, which are performed by an unauthorized user by means of optimal signal processing methods (optimal detection of biorthogonal signals), is analyzed in the article.

Improvement of Speech/Music Classification for 3GPP EVS Based on LSTM

The competition of speech recognition technology related to smartphones is now getting into full swing with the widespread internet of thing (IoT) devices. For robust speech recognition, it is necessary to detect speech signals in various acoustic environments. Speech/music classification that facilitates optimized signal processing from classification results has been extensively adapted as an essential part of various electronics applications, such as multi-rate audio codecs, automatic speech recognition, and multimedia document indexing. In this paper, we propose a new technique to improve robustness of a speech/music classifier for an enhanced voice service (EVS) codec adopted as a voice-over-LTE (VoLTE) speech codec using long short-term memory (LSTM). For effective speech/music classification, feature vectors implemented with the LSTM are chosen from the features of the EVS. To overcome the diversity of music data, a large scale of data is used for learning. Experiments show that LSTM-based speech/music classification provides better results than the conventional EVS speech/music classification algorithm in various conditions and types of speech/music data, especially at lower signal-to-noise ratio (SNR) than conventional EVS algorithm.

Model-Based Digital Pianos: From Physics to Sound Synthesis

As a result of their complexity and versatility, pianos are arguably one of the most important instruments in Western music. The size, weight, and price of grand pianos as well as their relatively simple control surface (i.e., the keyboard), have led to the development of digital counterparts that mimic the sound of acoustic pianos as closely as possible. While most commercial digital pianos are based on sample playback, it is also possible to reproduce a piano's sound by modeling the physics of the instrument. The process of physical modeling starts with first understanding the physical principles, followed by creating accurate numerical models, and finally, finding numerically optimized signal processing models that allow sound synthesis in real time by excluding inaudible phenomena and adding some perceptually important features by using signal processing tricks. Accurate numerical models can be used by physicists and engineers to understand how the instrument functions or to help piano makers with instrument development. On the other hand, efficient real-time models are geared toward composers and musicians who perform at home or onstage. This article provides an overview of a physics-based piano synthesis beginning with computationally heavy, physically accurate approach followed by a discussion of the approaches that are designed to produce the best possible sound quality for real-time synthesis.

Unusual Operation of the Junction Transistor Based on Dynamical Behavior of Impurities

The dynamical behavior of impurities into the silicon junction transistor has been studied using an empirical methodology to investigate its behavior knowing only the physical parameters of materials together with practical behavior of their passive components. The operating modes suggested with equations governing circuit performance are derived considering transient analysis. The relationship between material properties and equivalent circuit is discussed from a physical viewpoint. Theoretical solution of the equations yields a graphical response as approximation of the experimental results obtained from a proposed circuit built with an inductor and an NPN silicon MPSH10 transistor. Hence, the impurities-controlled electrical properties indicate that the observed unusual operation can be a good strategy to optimize signal processing in electronics.

Motion Capture Systems Using Optimal Signal Processing Algorithm: A State-of-the-art Literature

Motion capture system is a promising research area but the availability of the state-of-the-art literature review on this topic is limited. This research provides a comprehensive literature review for motion capture systems with Kalman filtering algorithms. The summarized state-of-the-art literature review of motion capturing system is being analyzed considering the advantages and the disadvantages of motion capture systems using Kalman filtering algorithm. Afterwards, the human body incorporating noises is represented by system of equations where the system states are unknown. The Kalman filter is adopted to estimate the human body orientations. Simulation results show that the proposed algorithm can be used to track human body orientation accurately.

Route, Modulation Format, MIMO, and Spectrum Assignment in Flex-Grid/MCF Transparent Optical Core Networks

In this paper, we target an optimal multiple-input multiple-output digital signal processing (MIMO-DSP) assignment to super-channels affected by intercore crosstalk (ICXT) in multicore fiber (MCF) enabled transparent optical core networks. MIMO-DSP undoes ICXT effects, but can be costly with high core density MCFs. Hence, its implementation in the network must be carefully decided. We address our objective as a joint route, modulation format, MIMO and spectrum assignment (RMMSA) problem, for which integer linear programming formulations are provided to optimally solve it in small network scenarios. Moreover, several heuristic approaches are also proposed to solve large-scale problem instances with good accuracy. Their goal is to minimize both network spectral requirements and the amount of MIMO equalized super-channels, taking a crosstalk-free space division multiplexing (SDM) solution as a reference, for example, based on parallel single mode fibers [i.e., a multifiber (MF) scenario]. For our evaluation, we consider several state-of-the-art MCF prototypes and different network topologies. The obtained results, with the considered MCFs, disclose that in national backbone networks, the desirable percentage of super-channels with MIMO equalization to match the performance of an equivalent crosstalk-free SDM solution ranges from 0% to 36, while in continental-wide networks this range raises from 0% to 56%. In addition, in the case of a nonideal MIMO (with a 3 dB/km of crosstalk compensation), such percentages range from 0% to 28% and from 0% to 45% in national and continental-wide backbone networks, respectively, experimenting a performance gap up to 12% with respect to the MF reference scenario.

An Optimal Algorithm for the Formation of Unbiased Estimates of the Effective Noise Temperature of a Stochastic Radio Thermal Signal

The main optimal signal processing operation is shown to be the division of the energy estimates for the random processes observed in the adjacent time intervals. It is justified that this processing may be deemed the primary one and it is necessary to introduce the secondary processing - averaging the unbiased primary estimates of the effective noise temperature. The potential fluctuation sensitivity of the radiometer and the limiting errors of the joint estimates of the noise temperature and the gain instability parameter have been determined.

Electrophysiological evidence for long-axis intrinsic diversification of the hippocampus.

The elongated structure of the hippocampus is critically involved in brain functions of profound importance. The segregation of functions along the longitudinal (septotemporal or dorsoventral) axis of the hippocampus is a slowly developed concept and currently is a widely accepted idea. The segregation of neuroanatomical connections along the hippocampal long axis can provide a basis for the interpretation of the functional segregation. However, an emerging and growing body of data strongly suggests the existence of endogenous diversification in the properties of the local neural network along the long axis of the hippocampus. In particular, recent electrophysiological research provides compelling evidence demonstrating constitutively increased network excitability in the ventral hippocampus with important implications for the endogenous initiation and propagation of physiological hippocampal oscillations yet, under favorable conditions it can also drive the local network towards hyperexcitability. In addition, important specializations in the properties of dorsal and ventral hippocampal synapses may support an optimal signal processing that contributes to the effective execution of the distinct functional roles played by the two hippocampal segments.