Coding Of Signals Research Articles

ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ НЕЙРОННЫХ СЕТЕЙ В ЗАДАЧАХ РАСПОЗНАВАНИЯ

The article describes the issues of increasing the efficiency of neural networks in terms of their design and coding of input and output signals. The application of multiple signal coding using extrapolation of the input parameters is described on the example of a system of recognition character sequences on images of arbitrary size with a complex background. An effective combination of multiple positional and configuration-competitive coding for various types of signals makes it possible to achieve performance rates of the building number recognition algorithm of up to 74 images per second in the adaptive learning mode and 218 images per second in the recognition only mode. The paper also outlines general recommendations for signal coding in artificial intelligence systems based on neural networks.

Average reward rates enable motivational transfer across independent reinforcement learning tasks

Outcomes and feedbacks on performance may influence behavior beyond the context in which it was received, yet it remains unclear what neurobehavioral mechanisms may account for such lingering influences on behavior. The average reward rate (ARR) has been suggested to regulate motivated behavior, and was found to interact with dopamine-sensitive cognitive processes, such as vigilance and associative memory encoding. The ARR could therefore provide a bridge between independent tasks when these are performed in temporal proximity, such that the reward rate obtained in one task could influence performance in a second subsequent task. Reinforcement learning depends on the coding of prediction error signals by dopamine neurons and their downstream targets, in particular the nucleus accumbens. Because these brain regions also respond to changes in ARR, reinforcement learning may be vulnerable to changes in ARR. To test this hypothesis, we designed a novel paradigm in which participants (n = 245) performed two probabilistic reinforcement learning tasks presented in interleaved trials. The ARR was controlled by an "induction" task which provided feedback with a low (p = 0.58), a medium (p = 0.75), or a high probability of reward (p = 0.92), while the impact of ARR on reinforcement learning was tested by a second "reference" task with a constant reward probability (p = 0.75). We find that performance was significantly lower in the reference task when the induction task provided low reward probabilities (i.e., during low levels of ARR), as compared to the medium and high ARR conditions. Behavioral modeling further revealed that the influence of ARR is best described by models which accumulates average rewards (rather than average prediction errors), and where the ARR directly modulates the prediction error signal (rather than affecting learning rates or exploration). Our results demonstrate how affective information in one domain may transfer and affect motivated behavior in other domains. These findings are particularly relevant for understanding mood disorders, but may also inform abnormal behaviors attributed to dopamine dysfunction.

Randomly Flipped Chip based signal power authentication for GNSS civilian signals

The navigation signal authentication schemes protect GNSS services from spoofing attacks by attaching unforgeable information to signals. In this study, Randomly Flipped Chip based Signal Power Authentication (RFC-SPA), is proposed to jointly authenticate the navigation message and spreading code of GNSS civilian signals. Designed to support two modes of authentication (fast channel and slow channel), the proposed scheme employs a fixed amount of flipped chips, which are randomly distributed in some areas of the spreading code to form a relative fluctuation in the correlation result of the signal. The fast channel is a spreading code authentication (SCA) of these flipped chips, which is the same as the Chimera. In the slow channel, since the correlation results between the local periodical spreading code and the signal in areas with flipped chips will be smaller than those results in areas without flipped chips, receivers in the tracking correlation can extract this fluctuation. Since the fluctuation modulates a digital signature, receivers can verify the authenticity of both the navigation message and spreading code through the authentication of this digital signature. Compared with mainstream schemes, RFC-SPA requires no extra tracking channel and has no impact on the navigation message. Besides, the proposed scheme maintains a similar robustness and security performance while significantly reducing the storage requirement compared with SCA. The scheme is demonstrated in a proposed implementation for Beidou B1C civilian signal, and the performance metrics are analysed. In the proposed implementation, the detection possibility is higher than 99.7% at 35dBHz of C/N0, and only 33.6% of the storage is required compared with the suggested configuration of the Chimera scheme for the GPS L1C civilian signal.

Deciphering the impact of genetic variation on human polyadenylation using APARENT2

Background3′-end processing by cleavage and polyadenylation is an important and finely tuned regulatory process during mRNA maturation. Numerous genetic variants are known to cause or contribute to human disorders by disrupting the cis-regulatory code of polyadenylation signals. Yet, due to the complexity of this code, variant interpretation remains challenging.ResultsWe introduce a residual neural network model, APARENT2, that can infer 3′-cleavage and polyadenylation from DNA sequence more accurately than any previous model. This model generalizes to the case of alternative polyadenylation (APA) for a variable number of polyadenylation signals. We demonstrate APARENT2’s performance on several variant datasets, including functional reporter data and human 3′ aQTLs from GTEx. We apply neural network interpretation methods to gain insights into disrupted or protective higher-order features of polyadenylation. We fine-tune APARENT2 on human tissue-resolved transcriptomic data to elucidate tissue-specific variant effects. By combining APARENT2 with models of mRNA stability, we extend aQTL effect size predictions to the entire 3′ untranslated region. Finally, we perform in silico saturation mutagenesis of all human polyadenylation signals and compare the predicted effects of {>}43 million variants against gnomAD. While loss-of-function variants were generally selected against, we also find specific clinical conditions linked to gain-of-function mutations. For example, we detect an association between gain-of-function mutations in the 3′-end and autism spectrum disorder. To experimentally validate APARENT2’s predictions, we assayed clinically relevant variants in multiple cell lines, including microglia-derived cells.ConclusionsA sequence-to-function model based on deep residual learning enables accurate functional interpretation of genetic variants in polyadenylation signals and, when coupled with large human variation databases, elucidates the link between functional 3′-end mutations and human health.

РАЗРАБОТКА АДАПТИВНОЙ СИСТЕМЫ СВЯЗИ НА ОСНОВЕ OFDM ДЛЯ ТРОПОСФЕРНОГО И РАДИОРЕЛЕЙНОГО КАНАЛА

It is known that inter-symbol interference may occur during data transmission in radio relayand tropospheric communication systems. The presence of multipath propagation, frequencyselectivefading and extreme instability in the tropospheric and radio relay channel significantlyreduces the energy efficiency of the communication system. The aim of the work was to increasethe efficiency of using the channel for radio relay and tropospheric communication by usingOFDM (orthogonal frequency-division multiplexing) signals in the system using adaptive codingand modulation. In the course of execution, the modulator and demodulator models of the OFDMsignal are implemented. When using various signal code structures in various reception/transmission conditions, it is possible to achieve optimal use of the frequency and energyresources, to create systems that adapt to the conditions of signal propagation. To implement thismechanism, a service field was introduced into the transmitted service data, which contains informationabout the code rate used, the modulation type, and the interleaving depth. This approachallows optimizing the use of energy and frequency resources. Together with the use of channelquality estimation algorithms, it becomes possible to dynamically change the signal-code structurewhen the reception conditions change. By adjusting the interleaving depth, it is possible to optimizethe S/N threshold or the amount of information delay in the channel, depending on the systemrequirements. The use of adaptive choice of code rate and modulation will allow more efficient useof the channel resource with a constant change in its state. The obtained results will significantlyincrease the energy efficiency of the OFDM system, lead to stable communication in nonstationarychannels and increase the throughput.

Combinatorial and antagonistic effects of tubulin glutamylation and glycylation on katanin microtubule severing.

Microtubules have spatiotemporally complex posttranslational modification patterns. How cells interpret this tubulin modification code is largely unknown. We show that C.elegans katanin, a microtubule severing AAAATPase mutated in microcephaly and critical for cell division, axonal elongation, and cilia biogenesis, responds precisely, differentially, and combinatorially to three chemically distinct tubulin modifications-glycylation,glutamylation, and tyrosination-but is insensitive to acetylation. Glutamylation and glycylation are antagonistic rheostats with glycylation protecting microtubules from severing. Katanin exhibits graded and divergent responses to glutamylation on the α- and β-tubulin tails, and these act combinatorially. The katanin hexamer central pore constrains the polyglutamate chain patterns on β-tails recognized productively. Elements distal to the katanin AAA core sense α-tubulin tyrosination, and detyrosination downregulates severing. The multivalent microtubule recognition that enables katanin to read multiple tubulin modification inputs explains invivo observations and illustrates how effectors can integrate tubulin code signals to produce diverse functional outcomes.

Improvement of Automotive Sensors by Migrating AUTOSAR End-to-End Communication Protection Library into Hardware

This paper explores new methods to increase the level of safety of data transfer between sensors and electronic control units (ECUs) in automotive communication. A new model of basic sensors to be used in automotive electronics is proposed. This model contains hardware modules that implement the end-to-end communication protection (E2E) mechanism, as defined by the Automotive Open System Architecture (AUTOSAR) standard. By adding this feature inside the sensors, it is possible that, in addition to increasing the safety level, these sensors can be directly connected to the network ECUs via standard communication buses (e.g., Local Interconnect Network (LIN), Controller Area Network (CAN), Flexray, etc.). This paper describes the model, design, and mapping (in a Field Programmable Gate Array device (FPGA)) of the hardware E2E module capable of generating the Cyclic Redundancy Code (CRC) and counter signal for a customized message. This message represents the output of the new sensor E2E module used in a safety communication as requested by the automotive E2E standard. The model is validated also by comparing the data output of the E2E hardware with the data output of the AUTOSAR software E2E library. Finally, future needs and directions are suggested in this area.

Photonic Generation of a Windowed Phase-Coded Microwave Waveform With Suppressed Spectrum Sidelobes

An approach to photonic generation of a windowed binary phase-coded microwave waveform with suppressed spectrum sidelobes is proposed and demonstrated. An optical double sideband plus carrier signal with the carrier and the two sidebands being orthogonally polarized is generated by a dual-polarization quadrature phase shift keying (DP-QPSK) modulator, with the generated signal sent to a phase modulator (PM) where phase coding is performed. The PM can support phase modulation in two orthogonal polarization directions. The phase-modulated signals are projected to one polarization direction and detected at a photodetector (PD). Switching the polarity of the coding signal, a π phase shift is introduced. Since the amplitude of the generated signal is dependent on the amplitude of the input coding signal, a windowing function is applied to the generated waveform by using a windowed input phase coding signal, to suppress the sidelobes in the spectrum of the generated microwave waveform. The key features of the proposed waveform generator include all-optical generation without the need of electronic components and optical filters, thus ensuring a wide operating frequency range. The proposed phase-coded microwave waveform generator also has the ability to switch between the fundamental and harmonic carrier frequency by controlling the modulator bias voltages. Experimental results show that, using a windowed 64-bit Gaussian pseudo-random binary sequence coding signal, a phase-coded microwave waveform is generated with the sidelobes of the spectrum largely suppressed by 20 dB and a pulse compression ratio as large as 133. Generation of binary phase-coded microwave waveforms at the 2nd harmonic carrier frequencies is also demonstrated experimentally.

Online Control Method of Small- and Medium-Sized Electromechanical Equipment Based on Deep Neural Network

In order to improve the online control effect of small- and medium-sized electromechanical equipment, this paper studies the online control method of small- and medium-sized electromechanical equipment combined with the deep audit network. Moreover, starting from the signal basis of online control signal recognition and channel coding recognition of electromechanical equipment, this paper determines the type of online control signal and channel coding type of electromechanical equipment required for the experiment. This paper compares the signals under different types of online control signals for electromechanical devices and clarifies the differences in amplitude, frequency, phase, and spectrum in time-domain waveforms. In addition, through the elaboration of different channel coding theories, this paper clarifies the differences in coding methods. Through the experimental research, it can be seen that the online control effect of the small- and medium-sized electromechanical equipment based on the deep neural network proposed in this paper is very good.

Penetration Depth Analysis of UMTS Networks Using Received Signal Code Power

This paper examines the coverage of three UMTS networks in Calabar, using the received signal code power (RSCP). A drive test conducted with the aid of a TEMS investigation software, collected log files of RSCP which were analyzed as coverage plots by a TEMS discovery software and further put through statistical measures using excel. The low values of calculated standard error depicts that the data used in this study is accurate and not manipulated. The data distribution in MTN and 9mobile network were slightly leptokurtic but slightly mesokurtic for Airtel network. Again, the data distribution for the three networks were approximately symmetric. Finally, 81.5%, 96.36% and 92.1% of the drive test routes for 9 mobile, Airtel and MTN network met with the NCC performance threshold. The result of this study will assist RF engineers in the optimization of UMTS networks and also in designing propagation models for accurate transmission of UMTS network signals in the study area.

Nonlinear Fourier transform receiver based on a time domain diffractive deep neural network

A diffractive deep neural network (D2NN) is proposed to distinguish the inverse nonlinear Fourier transform (INFT) symbols. Different from other recently proposed D2NNs, the D2NN is fiber based, and it is in the time domain rather than the spatial domain. The D2NN is composed of multiple cascaded dispersive elements and phase modulators. An all-optical back-propagation algorithm is proposed to optimize the phase. The fiber-based time domain D2NN acts as a powerful tool for signal conversion and recognition, and it is used in a receiver to recognize the INFT symbols all optically. After the symbol conversion by the D2NN, simple phase and amplitude measurement will determine the correct symbol while avoiding the time-consuming NFT. The proposed device can not only be implemented in the NFT transmission system, but also in other areas which require all optical time domain signal transformation and recognition, like sensing, signal coding and decoding, beam distortion compensation and image recognition.

Исследование асимптотической последовательности высот правильных симплексов при увеличении размерности евклидова пространства

The problem of spherical packing and the problem of the distribution of points on a sphere are well-known unsolved mathematical problems. In particular, the problem of the distribution of points on a sphere is included in the well-known list of unsolved mathematical problems of Steve Smale. Accordingly, a significant interest for the study is both the direct search for solutions to problems and research in areas related to known problems. In particular, the problem of spherical dense packing and coating packing is directly related to the study of regular, irregular and layered lattices, problems of noise-resistant coding, synthesis and analysis of broadband signals, mathematical research of multidimensional spaces, crystallography, methods for solving differential equations and calculating n-dimensional integrals, and many other particular problems and entire fields of knowledge. The paper presents the results of studies of some properties of n-dimensional regular simplex in Euclidean space. The vectors forming the n-dimensional regular simplex define the fundamental basis of the hexagonal lattice. The subject of the study is some properties and regularities of a vector object forming a regular simplex in n-dimensional Euclidean space, the novelty of the results lies in a formulated and proven theorem, several formulas that allow recursive and non-recursive calculations of some characteristics of n-dimensional regular simplex and spherical hexagonal packages. The object of the study is an n-dimensional regular simplex. Main results a theorem on the asymptotic character of the sequence of heights of regular simplex with increasing dimension of space is formulated and proved, the consequences of the theorem and remarks supplementing the theorem are formulated. The conclusion of the article contains additions and numerical examples with comments for some research results. The practical significance lies in the proposed mathematical tools that contribute to the development of the theory of spherical packing and the study of the properties of geometric objects in n-dimensional Euclidean space.

Compressing English Speech Data with Hybrid Methods without Data Loss

Understanding the mechanism of speech formation is of great importance in the successful coding of the speech signal. It is also used for various applications, from authenticating audio files to connecting speech recording to data acquisition device (e.g. microphone). Speech coding is of vital importance in the acquisition, analysis and evaluation of sound, and in the investigation of criminal events in forensics. For the collection, processing, analysis, extraction and evaluation of speech or sounds recorded as audio files, which play an important role in crime detection, it is necessary to compress the audio without data loss. Since there are many voice changing software available today, the number of recorded speech files and their correct interpretation play an important role in detecting originality. Using various techniques such as signal processing, noise extraction, filtering on an incomprehensible speech recording, improving the speech, making them comprehensible, determining whether there is any manipulation on the speech recording, understanding whether it is original, whether various methods of addition and subtraction are used, coding of sounds, the code must be decoded and the decoded sounds must be transcribed. In this study, first of all, what sound coding is, its purposes, areas of use, classification of sound coding according to some features and techniques are given. Moreover, in our study speech coding was done on the English audio data. This dataset is the real dataset and consists of approximately 100000 voice recordings. Speech coding was done using waveform, vocoders and hybrid methods and the success of all the methods used on the system we created was measured. Hybrid models gave more successful results than others. The results obtained will set an example for our future work.

Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex

Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and invitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under invivo conditions, but that background synaptic noise is actually beneficial.

Scattering of plane-wave and twisted photons by helical media

By using quantum electrodynamics in a dispersive medium, we describe scattering of plane-wave and twisted photons by a slab made of a helical medium, the helix axis being normal to the slab plane and the medium being not translation invariant in this plane, in general. In the particular cases, the permittivity tensor of a helical medium corresponds to cholesteric liquid crystals, C*-smectics, biaxial chiral nematics and smectics, Q-plates, chiral sculptured thin films, and helical dislocations. Both perturbative and nonperturbative approaches are considered. The explicit expressions for scattering amplitudes, probabilities, and Stokes parameters of photons are found taking into account the form of the photon wave packet. The selection rules are established showing that the helical medium transfers the momentum and the angular momentum to scattered photons. This property can be employed for production of twisted photons with large projection of the total angular momentum. We describe the device for shifting the projection of the total angular momentum of a photon and the principal scheme for signal coding in terms of twisted photons.

Analysis and Performance Evaluation of BDS-3 Code Ranging Accuracy Based on Raw IF Data from a Zero-Baseline Experiment

China’s BDS-3 global navigation satellite system has been built and is providing official open Positioning, Navigation, and Timing (PNT) service with full operational capability (FOC) since July 2020. The main new civil B1C and B2a ranging code signals are broadcasted on the two carriers with central frequencies of 1575.42 MHz and 1176.45 MHz, which were shared by other GNSSs. Compared with traditional signals, such as GPS L1 C/A and BDS B1I, the new civil signals have better modulation and wider bandwidth to be expected to achieve a better range performance. In order to evaluate code ranging accuracies directly, a zero-baseline experiment using a geodetic GNSS antenna and a four-channel intermediate frequency (IF) signal recorder was conducted. Two channels were used to receive the signals with a central frequency of 1575.42 MHz at a 62 MHz sampling rate, and the other two channels are for 1176.45 MHz. The raw IF data were post-processed using a software-defined receiver (SDR) to compute the code signal path differences between two channels with the same frequencies. Compared with the traditional hardware receiver, SDR has the characteristics of flexible use and good operability, but its running speed is slow. The root-mean-square (RMS) and bias values of the path differences from BDS B1C, BDS B2a, and GPS L5C were used to evaluate their accuracies. The results show that there is a weak negative correlation between the satellite elevation and the ranging accuracy when the satellite elevation ranges from 30° to 90°. The ranging accuracy of the B1C signal is lower than that of B2a, which may be caused by different code rates, bandwidth, and signal structure. The GPS L5C is used for precision analysis as a comparison. It shows that the code signal path differences accuracy of L5C is close to the B2a.

Through-Wall Human Motion Recognition Using Random Code Radar Sensor With Multi-Domain Feature Fusion

A random code radar sensor with multi-domain feature fusion is proposed and demonstrated experimentally for through-wall human motion recognition. This radar sensor transmits the aperiodic physical random code signal generated from the Boolean chaos as the probe signal, which can realize the anti-interference and unambiguous detection. The slow time-range (ST-R), slow time-Doppler frequency (ST-DF), and range-Doppler frequency (R-DF) maps are obtained by the correlation ranging, short-time Fourier transform (STFT), and fast Fourier transform (FFT), respectively. Furthermore, the features of ST-R, ST-DF, and R-DF domains are extracted by the fast principal component analysis, and fused by a simple serial connection to realize the complementarity and perfection of multi-domain features. Finally, the motion recognition is implemented with the support vector machine multi-classifier. The results show that utilizing the anti-interference random code signal and serial feature fusion, the proposed radar sensor can accurately recognize the human motions behind the wall without massive calculation and high computer configuration, and the average accuracies reach 97.22% for ten motions and 93.08% for six volunteers. Compared with the features of single domain and two domains, the multi-domain feature based on serial fusion can improve the recognition accuracy quickly and efficiently.

Analysis of Signal Quality, Voice Service, and Data Access on Telkomsel And Indosat Providers in Pakisjaya District

Quality in communication is very important in activities in this modern era. It is expected that the expected network quality against network quality is actually not expected. Measurement of network performance is important to refer for users to choose the right operator for service providers to improve the quality of their service Drive Test Method is a method used to measure cellular network performance. The purpose of this study is to study the results of research between service providers. The parameters used in this analysis are Receive Signal Code Power (RSCP), Cell ID, Signal Noise Ratio (SNR), Upload Rate, and Download Rate. This parameter is used for the measurement process of the Drive Test method. While the tool used to collect the value of each Drive Test parameter by using an Android-based application, GNet Track Pro. The measurement results with GNet Track Pro are then processed with the Google Earth application as a measurement area. Research data collected in this analysis were 60 cases, with each village 20 data collected to continue processing with the Drive Test method. In this study, Telkomsel chose to excel in voice services with 150 successful numbers of 150 attempted calls. While Indosat excels in providing data access services and special signals in the village of Tanjungbungin.

Synaptopathy in Guinea Pigs Induced by Noise Mimicking Human Experience and Associated Changes in Auditory Signal Processing.

Noise induced synaptopathy (NIS) has been researched extensively since a large amount of synaptic loss without permanent threshold shift (PTS) was found in CBA mice after a brief noise exposure. However, efforts to translate these results to humans have met with little success—and might not be possible since noise exposure used in laboratory animals is generally different from what is experienced by human subjects in real life. An additional problem is a lack of morphological data and reliable functional methods to quantify loss of afferent synapses in humans. Based on evidence for disproportionate synaptic loss for auditory nerve fibers (ANFs) with low spontaneous rates (LSR), coding-in-noise deficits (CIND) have been speculated to be the major difficulty associated with NIS without PTS. However, no robust evidence for this is available in humans or animals. This has led to a re-examination of the role of LSR ANFs in signal coding in high-level noise. The fluctuation profile model has been proposed to support a role for high-SR ANFs in the coding of high-level noise in combination with efferent control of cochlear gain. This study aimed to induce NIS by a low-level, intermittent noise exposure mimicking what is experienced in human life and examined the impact of the NIS on temporal processing under masking. It also evaluated the role of temporal fluctuation in evoking efferent feedback and the effects of NIS on this feedback.

Optic nerve repair and regeneration in vertebrates

<p indent="0mm">Vision is one of the major pathways for receiving external information in vertebrates. The optic nerve connects the retina to the brain and relays visual coding signals to the corresponding cortical regions. It is widely believed that the retinal ganglion cells (RGCs) and optic nerve cannot regenerate in mammals, and their injuries are the most common causes of blindness. Several extrinsic and intrinsic factors limit axonal regeneration in the optic nerve. Elimination of extrinsic inhibitory factors and activation of intrinsic pro-regenerative factors enable a small number of damaged axons to regenerate and improve visual functions in a limited manner. Furthermore, transplantation of stem cell-derived RGCs or <italic>in vivo</italic> reprogramming of Müller and amacrine cells into RGCs can restore part of the vision, which provides insights into the future therapy for various neurodegenerative disorders, such as glaucoma. This review summarizes the recent studies on axon and retinal cell regeneration after optic nerve injury in vertebrates.