Periodic Sequence Research Articles

Suppressing Voltage Spikes of MOSFET in H-Bridge Inverter Circuit

Power electronics devices are made from semiconductor switches such as thyristors, MOSFETs, and diodes, along with passive elements of inductors, capacitors, and resistors, and integrated circuits. They are heavily used in power processing for applications in computing, communication, medical electronics, appliance control, and as converters in high power DC and AC transmission in what is now called harmonized AC/DC networks. A converter’s operation is described as a periodic sequencing of different modes of operation corresponding to different topologies interfaced to filters made of passive elements. The performance of converters has improved considerably using high switching frequency, which leads to a significant improvement in a power converter’s performance. However, the high dv/dt through a fast-switching transient of the MOSFET is associated with parasitic components generating oscillations and voltage spikes having adverse effects on the operation of complementary switches, thereby affecting the safe operation of the power devices. In this paper, the MOSFET gate-driver circuit performance is improved to suppress the H-Bridge inverter’s voltage spikes. The proposed technique is a simple improvement to the gate driver based on the IR2112 driver (IC) by adding a capacitor to attenuate the effect of parasitic components and the freewheeling current, suppressing the negative voltage spikes. This paper’s main contribution is to improve the gate driver circuit’s capability for suppressing the voltage spikes in the H-Bridge inverter. The improved gate driver circuit is validated experimentally and is compared with the conventional gate driver. The experimental results show that the proposed technique can effectively suppress the MOSFET’s voltage spikes and oscillations.

Cluster mean-field theory studies of the frustrated two-dimensional quantum-mechanical [formula omitted] Heisenberg model

The phase diagrams of the two-dimensional quantum-mechanical Heisenberg model with antiferromagnetic nearest and next-nearest neighbor exchange interaction is investigated with the cluster mean-field theory. The four different scenarios considered are the J1−J2 model with only S=1∕2 spins, the J1−J2 model with only S=1 spins, and the mixed S=1∕2 and S=1J1−J2 model. Within the ferrimagnetic J1−J2 model, two different configurations of the spin order are assumed and investigated: checkerboard-like order of the S=1∕2 and S=1 spins, and a line order, where the S=1∕2, respectively, S=1 sublattice spins are ordered along lines which itself are ordered in a periodic sequence. The phase diagrams are characterized by calculating the energy per atom E and the magnetization m=|〈Sz〉|. In the antiferromagnetic S=1∕2J1−J2 model, the quantum states and the entanglement (von Neumann entropy) are investigated as a function of J2∕J1.

Pulse radar randomly interrupted transmitting and receiving optimization based on genetic algorithm in radio frequency simulation

The interrupted transmitting and receiving (ITR) can be used in anechoic chamber to solve the coupling between the transmitted and reflected signals. When the ITR periods are random, the fake peaks in high-resolution range profile (HRRP) of ITR echo can be reduced. Then, by utilizing the piecewise sparse property of ITR echo, the HRRP is reconstructed based on compressive sensing (CS). However, the periods of ITR determine the restricted isometry property (RIP) condition and the HRRP reconstruction performance. In order to improve the HRRP reconstruction performance, the ITR period sequence optimization method based on a genetic algorithm (GA) is proposed in this paper. The correlation coefficient of the sensing matrix columns is minimized after optimization so that the RIP of the sensing matrix can be well satisfied. Simulation and comparison results illustrate that the optimization method converges fast and the HRRP reconstruction performance is improved with the optimized ITR periods.

Construction of Gaussian Integer Periodic Complementary Sequence Set with Zero Correlation Zone

Based on aperiodic complementary sequence (ACS) sets and orthogonal matrices, the construction of Gaussian integer (GI) zero correlation zone (ZCZ) periodic complementary sequence (ZPCS) sets is proposed. The constructed GI ZPCS sets can achieve the theoretical bound, and the length of ZCZ can be chosen flexibly. The GI ZPCS sets obtained by this paper can be used in multi-carrier code division multiple access system to obtain higher spectrum efficiency and eliminate interference.

Use of the dry-spell seasonal forecast in crop management decisions

Climate forecasts have shown the potential for improving the resilience of agriculture to climate change. The usefulness of climate forecasts for applications in agriculture can be enhanced if the forecasts are translated into agricultural outlooks, in which the information is targeted for decision-making. The sequence of dry periods is necessary for successful crop management decisions, especially in dry season planting. This paper investigates how well the Climate Forecast System version 2 (CFSv2) seasonal forecasts predict the dry spell (DS) over the Indonesia region. The seasonal forecasts were downscaled using the constructed analogue method and, in turn, were corrected with TRMM 3B42 rainfall data to match daily precipitation totals. The DS is defined as rainfall less than 5 mm day−1 for ≥10 consecutive days. Accuracy of the DS prediction was assessed using the Brier Score (BS) method for December-January-February (DJF) and June-July-August (JJA) periods. The results demonstrate that the highest accuracy of the DS forecast occurred in JJA in southern part Indonesia with a range of the BS value between 0-0.2 (>80%). The operational DS seasonal forecasts are needed to manage agriculture practices for the upcoming planting season such as the choice of a crop/variety, supplementary irrigation, and crop water requirement.

Coherence of a dynamically decoupled single neutral atom

Long qubit coherence and efficient atom–photon coupling are essential for advanced applications in quantum communication. One technique to maintain coherence is dynamical decoupling (DD), where a periodic sequence of refocusing pulses is employed to reduce the interaction of the system with the environment. We experimentally study the implementation of DD on an optically trapped, spin-polarized 87 R b atom. We use the two magnetic-sensitive 5 S 1 / 2 Zeeman levels | F = 2 , m F = − 2 ⟩ and | F = 1 , m F = − 1 ⟩ as qubit states, motivated by the possibility of coupling | F = 2 , m F = − 2 ⟩ to 5 P 3 / 2 the excited state | F ′ = 3 , m F ′ = − 3 ⟩ via a closed optical transition. With more refocusing pulses in the DD technique, we manage to extend the coherence time from 38(3) µs to around 7 ms. We also observe a strong correlation between the motional states of the atom and the qubit coherence after the refocusing, which can be used as a measurement basis to resolve trapping parameters.

Generation of a Periodic Sequence of Ultrashort Electromagnetic Pulses in a Scheme with Two Parallel Radiating and Absorbing Electron Beams

We demonstrate the possibility of generating a periodic sequence of ultrashort electromagnetic microwave pulses in a scheme with two parallel coaxial electron beams formed by a common cathode and transported via common vacuum channel. The external cylindrical tubular beam ensures the amplification of radiation during rectilinear propagation along periodic slow-wave system, while the internal (paraxial) beam accounts for the nonlinear cyclotron-resonance absorption.

Risk of short-term biodiversity loss under more persistent precipitation regimes.

Recent findings indicate that atmospheric warming increases the persistence of weather patterns in the mid-latitudes, resulting in sequences of longer dry and wet periods compared to historic averages. The alternation of progressively longer dry and wet extremes could increasingly select for species with a broad environmental tolerance. As a consequence, biodiversity may decline. Here we explore the relationship between the persistence of summer precipitation regimes and plant diversity by subjecting experimental grassland mesocosms to a gradient of dry-wet alternation frequencies whilst keeping the total precipitation constant. The gradient varied the duration of consecutive wet and dry periods, from 1 up to 60days with or without precipitation, over a total of 120days. An alternation of longer dry and wet spells led to a severe loss of species richness (up to -75% relative to the current rainfall pattern in W-Europe) and functional diversity (enhanced dominance of grasses relative to nitrogen (N)-fixers and non-N-fixing forbs). Loss of N-fixers and non-N-fixing forbs in severe treatments was linked to lower baseline competitive success and higher physiological sensitivity to changes in soil moisture compared to grasses. The extent of diversity losses also strongly depended on the timing of the dry and wet periods. Regimes in which long droughts (≥20days) coincided with above-average temperatures showed significantly more physiological plant stress over the experimental period, greater plant mortality, and impoverished communities by the end of the season. Across all regimes, the duration of the longest period below permanent wilting point was an accurate predictor of mortality across the communities, indicating that increasingly persistent precipitation regimes may reduce opportunities for drought stress alleviation. We conclude that without recruitment, which was precluded in this experiment, summer precipitation regimes with longer dry and wet spells will likely diminish plant diversity, at least in the short term.

АНАЛИЗ ЛИНЕЙНОЙ СЛОЖНОСТИ Q-ИЧНЫХ ОБОБЩЕННЫХ ЦИКЛОТОМИЧЕСКИХ ПОСЛЕДОВАТЕЛЬНОСТЕЙ ПЕРИОДА pn

The article presents the analysis of the linear complexity of periodic q-ary sequences when changing k of their terms per period. Sequences are formed on the basis of new generalized cyclotomy modulo equal to the degree of an odd prime. There has been obtained a recurrence relation and an estimate of the change in the linear complexity of these sequences, where q is a primitive root modulo equal to the period of the sequence. It can be inferred from the results that the linear complexity of these sequences does not sign ificantly decrease when k is less than half the period. The study summarizes the results for the binary case obtained earlier.

The 2-adic complexity of Yu-Gong sequences with interleaved structure and optimal autocorrelation magnitude

In 2008, a class of binary sequences of period \(N=4(2^k-1)(2^k+1)\) with optimal autocorrelation magnitude has been presented by Yu and Gong based on an m-sequence, the perfect sequence (0, 1, 1, 1) of period 4 and interleaving technique. In this paper, we study the 2-adic complexity of these sequences. Our result shows that it is larger than \(N-2\lceil \mathrm {log}_2N\rceil +4\) (which is far larger than N/2) and could attain the maximum value N if suitable parameters are chosen, i.e., the 2-adic complexity of this class of interleaved sequences is large enough to resist the Rational Approximation Algorithm.

Grain-like structures with minimal and maximal period sequences

Nonlinear feedback shift registers (NFSRs) are important building blocks for stream ciphers. The cascade connection of an n-stage full-length linear feedback shift register (LFSR) into an m-stage NFSR is called a Grain-like structure. In this paper, we focus on Grain-like structures which can generate minimal and maximal possible period sequences. The existence of Grain-like structures which can generate minimal possible period sequences is proved for the cases $$m=n$$ and $$m>n$$ . The number of such Grain-like structures is estimated in both cases. Two necessary conditions are presented for Grain-like structures to generate maximal possible period sequences. Moreover, some interesting properties of such Grain-like structures are discussed.

Multiplier dynamic data envelopment analysis based on directional distance function: An application to mutual funds

This paper extends the multiplier dynamic data envelopment analysis (DEA) by using directional distance function (DDF). Based on the duality theory, a multiplier network DDF model is proposed for the dynamic system which consists of a sequence of periods linked by carryovers. The proposed multiplier dynamic model is non-oriented and is able to handle negative data that possibly exist in inputs, carryovers and outputs. The overall efficiency score calculated by the proposed multiplier dynamic model can be decomposed into a weighted average of period efficiency scores. The approach that determines a unique efficiency score for each period is also proposed. To demonstrate the validity and practicality of the proposed dynamic model, we apply it to evaluate the performance of mutual funds in the American market. The empirical results show that the proposed multiplier dynamic model has strong ability to discriminate performance and good practice value for the actual portfolio selection.

On construction of almost periodic sequences and applications to some discrete population models

In this work, we develop a novel approximation strategy for building almost periodic sequences in the theory of almost periodic functions. Here, we create a different perspective for the argument of Dirichlet in the theory of numbers and design an integer approximation strategy in this regard. The idea behind the strategy comes from Kronecker's theorem and it is proven that for given an almost periodic function, it is possible to design its corresponding almost periodic sequence. Moreover, we provide two population models in both continuous and discrete cases where almost periodic sequence solutions are designed under suitable circumstances.

Mean boundedness, global attractivity and almost periodic sequence of stochastic neural networks with discrete-time analogue

A class of stochastic neural networks with discrete-time analogue is investigated in this paper. By employing contraction mapping principle and some stochastic analysis techniques, we establish some sufficient conditions for mean boundedness, global attractivity and almost periodic sequence of the model. An example and graphic illustrations are displayed to visually expound the main contributions. The research techniques in this literature are suitable for other stochastic models in science and engineering.

English

In this article, we define a new series transformation called transformation and probe into its fixed point and periodicity. We extend the number field of the transform period problem to a wider field. Different constraints are imposed on then different periodic columns are formed after finite transformations. We obtain that their periodic sequences are and respectively after derivation. As an application, it can provide a reference for C problems in more complex algebraic systems.

A Machine Learning Approach for Prediction of Signaling SIP Dialogs

In this paper, we propose a machine learning methodology for prediction of signaling sessions established with the Session Initiation Protocol (SIP). Given the increasing importance of predicting and detecting abnormal sequences of SIP messages to avoid SIP signaling-based attacks, we first propose a Bayesian inference method capable of representing the statistical relation between a SIP message, observed by a SIP user agent or a SIP server, and prior trustworthy SIP dialogs. The Bayesian inference method, a Hidden Markov Model (HMM) enriched with n-gram Markov observations, is updated over time, so the inference can be used in real-time. The HMM is then used for predicting and detecting SIP dialogs through a lightweight implementation of Viterbi algorithm for sparse state spaces. Experimental results are also reported, where a SIP dataset representing prior information collected by a SIP user agent and/or a SIP server is used to predict or detect if a received sequence of SIP messages is legitimate according to similar SIP dialogs already observed. Finally, we discuss the results obtained for a dataset of abnormal SIP sequences, not observed during the inference stage, showing the effective utility of the proposed methodology to detect abnormal SIP sequences in a short period of time.

Novel Hybrid Public/Private Key Cryptography Based on Perfect Gaussian Integer Sequences

This paper proposes a novel hybrid public/private key cryptography scheme based on perfect Gaussian integer sequences (PGISs) of period $N=pq$ . First, a review study of construction degree-4 PGIS is addressed. We show that circular convolution over PGISs is a trapdoor one-way permutation function that enables simultaneous cipher encryption and digital signatures. To implement the proposed cipher encryption scheme, a private PGIS is assigned as the encryption key sequence for circular convolution with the plaintext to generate the ciphertext. The reverse decryption key sequence involves the time reflection and complex conjugation of the encryption sequence, which can be regenerated using a pair of public and private keys. The security level of the proposed scheme is the same as that of the Rivest-Shamir-Adleman (RSA) system; however, the capacity of a cryptosystem based on PGISs may outperform that of based on RSA, because abundant PGISs are available. Simulation results show that the approximation error when finite digits are used to represent the irrational coefficients of a normalized PGIS can be relatively small compared with the noise. This contributes to the simplicity of this scheme’s implementation. With the fast development of IoT (internet of things), the adaptation and applicability of the proposed scheme to IoT platforms are also addressed, where lightweight cryptographic functions are preferable due to the limited resources of IoT devices.

КОНТРОЛЬНІ КАРТИ ШУХАРТА В ЗАДАЧАХ ДІАГНОСТИКИ СТАЛОГО РОЗВИТКУ ТЕРИТОРІЇ

Inconsistency and instability of planning processes are some of the important obstacles to achieving the goals of sustainable development of Ukraine today. This indicates the imperfection of the analytical function of the management system of sustainable development of the territory, which is associated with the forecasting and diagnosis of development processes. The thresholds of indicators for diagnosing the state of the territory by the level of stability (homeostasis) are fundamental, i.e. acceptable limit values, non-compliance (exceeding or not reaching) which leads to the emergence of destructive processes in the territory. The legislative approach is used in domestic practice to determine the threshold values of indicators, based on expert assessments of specialists. But the expert definition of these indicators is sufficiently subjective, which, in turn, does not preclude fundamental errors in diagnosing the state of the territory. In order to prevent subjectivism, it is advisable to use Shewhart control charts as a diagnostic tool to identify the uncontrolled state of the territory and answer the question: should or should not interfere with the system? The theory of control charts largely corresponds to the main provisions of the theories of sustainable development and «The Black Swan». Development is considered as a sequence of long periods in the theory of sustainable development, which is based on the basic principles of synergetic and nonlinear dynamics. These periods correspond to the stable states of the system (homeostasis), which are interrupted by periods of bifurcation (chaos). After a period of chaos, the system moves to the next qualitatively new steady state (attractor), the choice of which is usually determined by fluctuations (i.e., difficult to predict, new events, the so-called «Black Swans») at the bifurcation point. To study the problems of controllability of the process of sustainable development of the territory, the most suitable are Shewhart’s individuals control chart (X) and moving range (mR), which are used for periodic monitoring data and rapid detection of special causes (fluctuations). On the example of interpreting the results of XmR chart to diagnose the manageability of human development in Ukraine and Kuwait for 1990-2019 proved the feasibility of using a combined XmR chart in diagnosing the state of the territory on indicators or integrated indices that characterize various aspects of development.

Quaternion Fourier series of periodic pulse sequence

Quaternion Fourier series of periodic pulse sequence

Quaternion Fourier series of periodic pulse sequence

Quaternion Fourier series of periodic pulse sequence