Random Binary Sequence Research Articles

A Statistical Measurement of Randomness Based on Pattern Vectors

Randomness of data or signals has been applied and studied in various theoretical and industrial fields. There are many ways to define and measure randomness. The most popular one probably is the statistical testing for randomness. Among the approaches adopted, Runs Test is a highly used technique in testing the randomness. In this article, we demonstrate the inefficient aspects of Runs Test and put forward a new approach, or pattern-vector-based statistic, based on pattern vectors that could effectively enhance the precision of testing randomness. A random binary sequence is supposedly to have less or no patterns. Based on this, we put forward our randomness-testing statistic. We also run an experiment to demonstrate how to apply this statistic and compare the efficiency or failure rate with Runs Test in dealing with a set of randomly generated input sequences. Moreover, we devise a statistically-justifiable measure of randomness for any given binary sequence. In the end, we demonstrate a way to combine this new device with Kalman filters to enhance the data assimilation.

Moving Horizon Estimation for Uncertain Networked Control Systems with Packet Loss

This paper studies a moving horizon estimation approach to solve the constrained state estimation problem for uncertain networked systems with random packet loss. The system model error range is known, and the packet loss phenomena are modeled by a binary switching random sequence. Taking the model error, the packet loss, the system constraints, and the network transmission noise into account, a time-varying weight matrix is obtained by solving a least-square problem. Then, a robust moving horizon estimator is designed to estimate the system state by minimizing an optimization problem with an arrival cost function. The proposed estimator ensures that the optimal estimated state can be obtained in the worst case. Furthermore, the asymptotic convergence of the estimator is analyzed and some sufficient conditions for convergence are given. Finally, the validity of the proposed approach can be demonstrated by numerical simulations.

From prelife to life: a bio-inspired toy model

We study a one-dimensional lattice of N sites each occupied by a mathematical ‘polymer,’ that is, is a binary random sequence of arbitrary length n, or equivalently, a rooted path of n links on an infinite binary tree. The average polymer length is controlled by the monomer fugacity z. A pair of polymers on adjacent sites carries a weight factor ω for each link on the tree that they have in common. The phase diagram in the zω plane exhibits a critical line z = zc(ω). For z < zc(ω) there exists an equilibrium phase with, in particular, a finite average polymer length. We investigate the equilibrium ensemble by transfer matrix and Monte Carlo methods, paying particular attention to the vicinity of the critical line. For z > zc(ω) the equilibrium is unstable and Monte Carlo time evolution brings about a dynamical symmetry breaking which favors the evolution of a small selection of polymers to ever greater length. While of interest for its own sake, this model may also be relevant to the prelife-to-life transition that has occurred during biological evolution. We compare it to existing models of similar simplicity.

An Effective Semi-fragile Watermarking Method for Image Authentication Based on Lifting Wavelet Transform and Feed-Forward Neural Network

Digital watermarking is a significant issue in the field of information security and avoiding the misuse of images in the world of Internet and communication. This paper proposes a novel watermarking method for tamper detection and recovery using semi-fragile data hiding, based on lifting wavelet transform (LWT) and feed-forward neural network (FNN). In this work, first, the host image is decomposed up to one level using LWT, and the discrete cosine transform (DCT) is applied to each 2×2 blocks of diagonal details. Next, a random binary sequence is embedded in each block as the watermark by correlating DC coefficients. In the authentication stage, first, the geometry is analyzed by using speeded up robust features (SURF) algorithm and extract watermark bits by using FNN. Afterward, logical exclusive or operation between original and extracted watermark is applied to detect tampered region. Eventually, in the recovery stage, tampered regions are recovered using the inverse halftoning technique. The performance and efficiency of the method and its robustness against various geometric, non-geometric, and hybrid attacks are reported. From the experimental results, it can be seen that the proposed method is superior in terms of robustness and quality of the watermarked and recovered images, respectively, compared to the state-of-the-art methods. Besides, imperceptibility has been improved by using different correlation steps as the gain factor for flat (smooth) and texture (rough) blocks. Based on the advantages exhibited, the proposed method outperforms the related works, in terms of superiority, efficiency, and effectiveness for tamper detection and recovery-based applications.

Optimal communications with infinite impulse response matched filters

Abstract Optimal communication waveforms matched to a large and practically important class of filters are investigated and shown to be chaotic. Filters of this class are defined by an infinite impulse response (IIR) and a transfer function comprising a finite number of distinct stable poles. This class contains many of the most popular and widely used filter families, including Butterworth, Chebyshev (type I), and Bessel. For such a filter, a matched basis function is derived and convolved with a random binary sequence to construct a communication waveform. It is shown that this waveform is chaotic in the sense that it is deterministic and characterized by a positive Lyapunov exponent. This result supports a recent conjecture that optimal communication waveforms matched to stable IIR filters are chaotic, and it further establishes that chaos is fundamental to modern communication theory.

Integrated Partial Encryption and Watermarking Technique for Digital Video using Chaos and Support Images

Encryption and Watermarking are image processing tools that are used mostly separately. Encrypting a document completely obscures it and watermarking is applied mostly for copy right protection. For entertainment type videos, partial encryption and watermarking may be integrated such that both objectives are attained. We report in this paper a novel combined partial encryption and watermarking algorithm for digital videos using chaotic system and support image. Watermarks are generated by using iris information of the authentic user or the authentic producer of the digital video. Watermarks of full size and half size are embedded in the luminance frame (s) of the video using simple LSB steganography. A sequence of color frames is watermarked in two phases, and partially encrypted in two layers, the watermarks considered are encrypted before embedding. The luminance frame (s) is (are) preprocessed before embedding with the watermarks to defy stega-analysis. Chaotic logistic map and a gray level support digital image is used for obtaining unique row/column sequences as well as for generating robust random binary sequences. A support color digital image is used in the first layer encryption of the digital video. Modified Rabinovich 4 dimensional hyper-chaotic system is used for second layer encryption. Encryption algorithm is applied in R, G, B frames separately. The technique may also be applied for integrated encryption and watermarking of digital images.

THE GENERATING RANDOM SEQUENCES WITH THE INCREASED CRYPTOGRAPHIC STRENGTH

Random sequences are used in various applications in construction of cryptographic systems or formations of noise-type signals. For these tasks there is used the program generator of random sequences which is the determined device. Such a generator, as a rule, has special requirements concerning the quality of the numbers formation sequence. In cryptographic systems, the most often used are linearly – congruent generators, the main disadvantage of which is the short period of formation of pseudo-random number sequences. For this reason, in the article there is proposed the use of chaos generators as the period of the formed selection in this case depends on the size of digit net of the used computing system. It is obvious that the quality of the chaos generator has to be estimated through a system of the NIST tests. Therefore, detailed assessment of their statistical characteristics is necessary for practical application of chaos generators in cryptographic systems. In the article there are considered various generators and there is also given the qualitative assessment of the formation based on the binary random sequence. Considered are also the features of testing random number generators using the system. It is determined that not all chaos generators meet the requirements of the NIST tests. The article proposed the methods for improving statistical properties of chaos generators. The method of comparative analysis of random number generators based on NIST statistical tests is proposed, which allows to select generators with the best statistical properties. Proposed are also methods for improving the statistical characteristics of binary sequences, which are formed on the basis of various chaos generators.

Linear Transfer Functions Extraction for a Power Generation Three-Shaft Gas Turbine Based on Actual Specifications

The design and testing of various types of controllers require accurate and reliable transfer functions that are compatible with the performance condition of the system. In this paper, the linear and the nonlinear methods have been utilized for extracting the transfer functions for a three-shaft industrial gas turbine. The main variables are the fuel input and environment temperature, while the main outputs are the LPT exhaust gas temperature and the generated power. According to the nonlinear structure of the system and the input variation intervals, the quasi-amplitude-modulated pseudo random binary sequence signals have been utilized for generating input parameters. Finally, the results extracted from the selected methods were compared to the outputs of real performance data under loading and unloading conditions. Based on the comparison between the accuracies obtained by the results, the auto-regressive moving average with eXogenous, try and error transfer function and linearized Hammerstein model methods are proposed, respectively. The outcome of using the controller indicated higher compatibility from transfer functions as compared to the reference dynamic model.

An Experimental Study on Estimation of Inductive Load in Grid Connection Inverter by Pseudo Random Binary Sequence

An Experimental Study on Estimation of Inductive Load in Grid Connection Inverter by Pseudo Random Binary Sequence

Chaotic Image Encryption Using Hopfield and Hindmarsh-Rose Neurons Implemented on FPGA.

Chaotic systems implemented by artificial neural networks are good candidates for data encryption. In this manner, this paper introduces the cryptographic application of the Hopfield and the Hindmarsh–Rose neurons. The contribution is focused on finding suitable coefficient values of the neurons to generate robust random binary sequences that can be used in image encryption. This task is performed by evaluating the bifurcation diagrams from which one chooses appropriate coefficient values of the mathematical models that produce high positive Lyapunov exponent and Kaplan–Yorke dimension values, which are computed using TISEAN. The randomness of both the Hopfield and the Hindmarsh–Rose neurons is evaluated from chaotic time series data by performing National Institute of Standard and Technology (NIST) tests. The implementation of both neurons is done using field-programmable gate arrays whose architectures are used to develop an encryption system for RGB images. The success of the encryption system is confirmed by performing correlation, histogram, variance, entropy, and Number of Pixel Change Rate (NPCR) tests.

A Low Cost, Rapid Impedance Measurement Technique Suitable for Li-ion Health Diagnosis in Battery Energy Storage Systems

Battery energy storage is becoming a vital part of green energy systems. Prediction of the state of health of energy storage systems is difficult as it relies on a number of parameters. Pseudo Random Binary Sequence (PRBS) excitation of energy storage batteries has been shown to be a valid method of battery parameter identification for lead acid batteries [1]. The purpose of this work is to validate PRBS test data from a 3Ah LiFePO4 cell forming part of an EV battery-pack cell against Electrochemical Impedance Spectroscopy (EIS) data obtained from an industry-standard potentiostat (Solartron 1480). PRBS results are obtained in under 200 seconds on easily reproducible equipment which can be built into a green energy battery management system, while the EIS process takes over two hours on prohibitively expensive laboratory equipment. This work validates PRBS as a fast and portable method of obtaining the impedance spectrum of Lithium Ion cells, which can then be used to obtain information about SoH of the BESS.

Blind Image Watermarking for Localization and Restoration of Color Images

Digital images have become easy to generate and share with tremendous growth in communication technology. Therefore, the threat of forgery and tampering in digital images has also been increased. This study proposes a blind fragile watermarking scheme for color images to provide efficient image tamper detection and self-recovery. A secret key based pseudo random binary sequence is used as a fragile watermark for tamper detection. Likewise, the recovery information is preserved in a randomized manner using a secret key. During embedding, each channel of the RGB image is divided into non-overlapping 2 × 4 size blocks. Each block is then watermarked using a LSB (least significant bit) replacement process in 9-base notation structure. The watermark sequence (i.e. 12-bit) for each block contains 6-bits from the fragile watermark and concatenated with the recovery information (i.e. 6 MSB (most significant bit) of block's mean value) of a different block. The experimental results confirm that the scheme is highly efficient to locate tampered region and recover the original image even in case of serious tampering. The scheme offers nearly 99% accurate tamper detection and significant recovery of tampered images (up to 80% tampering rate). Comparative results prove the significance and superiority of the scheme over existing schemes.

Chaotic Binary Sequence Generator based on Logistic Map

Pseudorandom binary sequences find various applications in different areas such as security, communication, steganography and cryptography. The properties like sensitivity to initial condition, ergodicity, mixing property and dynamic behavior are used in the designing of random number generators known as chaotic systems. In this study, an efficient chaotic binary sequence generator using logistic map is proposed, implemented and analyzed. The proposed binary sequence generator generates 50 chaotic sequences by varying initial condition with fixed system parameter. Subsequently, the generated sequences are transformed to binary sequences using thresholding method. The output of binary sequences is statistically tested with FIPS 140-2 test suite in order to identify the specific properties expected for truly random binary sequences. The experimental results prove that the generated binary sequences possess identical characteristics of true random numbers and can pass all tests of FIPS 140-2 test suite.

Deep learning based system identification of industrial integrated grinding circuits

Energy efficiency and maximum productivity in ore beneficiation processes can be ensured when integrated grinding circuits function in an optimal fashion. The complexity of first principles based models prevents online implementation of control and optimization algorithms, thus, creating the need for the development of accurate data-based models. In this work, deep recurrent neural networks (DRNNs) are implemented for nonlinear system identification of 3 input 6 output integrated grinding circuit from an industrial lead-zinc ore beneficiation set-up. Optimal long short term memory networks (LSTMs) with maximum predictability are obtained by solving a novel multi-objective framework for DRNN architecture design. The optimal LSTMs are trained and validated on pseudo random binary sequence (PRBS) signal with an accuracy of 99%, and tested successfully on unseen random Gaussian sequence (RGS) signal. Comprehensive comparison with conventional tools for nonlinear system identification, such as wavelet networks, is performed to show the efficacy of proposed optimal LSTMs.

An Improved Area Efficient 16-QAM Transceiver Design using Vedic Multiplier for Wireless Applications

In this research article, an improved area efficient 16-Quadrature Amplitude Modulation (QAM) transceiver design is introduced using Vedic multiplier. The 16-QAM design is transmitted using Pseudo Random Binary Sequence (PRBS) and modulated by changeable clock frequencies. The Vedic multiplier uses Urdhva Tiryakbhyam (Vertical and Crosswise) method of multiplication to reduce the undesirable steps and generates parallel partial products. Compressor adders are used in the Vedic multipliers, which helps to increase the speed of multiplication process and reduces the carry delay. Four Compressor adders namely 5-3, 10-4, 15-4 and 20-5 are used in a 16-bit Urdhva Tiryakbhyam Vedic multiplier to add its partial products. The proposed 16-QAM design is implemented using Spartan-3 XC3S200-5 pq208 Field Programmable Gate Array (FPGA) device which occupies 672 slices, 1102 4-input Look up Tables (LUTs) and 39 mW of power consumption. The Vedic multiplier based 16-QAM transceiver design reduces 17.2% slices and 4.5% 4-input LUTs. The 16-QAM is a preferred digital modulation method in the Orthogonal Frequency Division Multiplexing (OFDM) system, which reduces bit errors and noise effects during data transmission. The OFDM transceiver design is used in the high-speed wireless communication by excellence of its Multi-carrier modulation method.

Theory and experiments based on tracked moving flexible DOE loops for speckle suppression in compact laser projection

This paper describes a speckle suppression method using flexible diffractive optical elements (DOEs) based on binary random sequences with tracked motion. The DOE loops consist of 1D random-sequence diffractive structures with similar but different inclination angles. A mathematical approach for determining the optimal inclination angles and DOE speed for speckle suppression is developed, and a model for calculating the speckle suppression efficiency is constructed. Theoretical and experimental results show that the proposed method decreases the speckle contrast to below the sensitivity of the human eye, making it suitable for compact laser projections. The experimental results also indicate that current DOE production technology should be improved to avoid limiting the image quality.

A 40-GHz Mirrored-Cascode Differential Transimpedance Amplifier in 65-nm CMOS

This paper presents a fully differential transimpedance amplifier (TIA) realized in a standard 65-nm CMOS process, where a novel mirrored-cascode (MC) input configuration is proposed for differential signaling, i.e., an NMOS cascode amplifier with a resistive feedback for negative output and its MC amplifier via an ac-coupling capacitor for positive output. For bandwidth extension, the third-order asymmetric transformers were carefully employed. Measured results of the proposed MC differential (MCD) TIA demonstrate 54-dB $\Omega $ transimpedance gain, 40-GHz bandwidth for 50-fF photodiode capacitance, $19.8-\text{pA}/\sqrt {\mathrm {Hz}}$ average noise current spectral density, ±10-ps group delay variation, and 55.2-mW power consumption. Eye diagrams for 32 Gb/s 215 –1 pseudo random binary sequence (PRBS) were measured with the input currents of 100–1.5 mApp. The chip occupies the area of 0.6 mm2 including I/O pads.

Optimized Modeling of Flexible Beam Structure with Pole-Zero Estimation

In this paper, the optimized mathematical model that represents a flexible beam structure is developed via system identification technique utilizing Artificial Bee Colony (ABC) and Firefly Algorithm (FFA). The flexible beam structure is a common element applied in various fields of engineering and industries. To model the structure, the input and output data are collected experimentally from a well-developed test rig within MATLAB Simulink platform. In order to detect multiple resonance modes, Pseudo Random Binary Sequence (PRBS) signal which contains a wide range of bandwidth frequency is applied as the disturbance force. The best fit of the predicted model is obtained with respect to the minimum value of mean square error (MSE) and the accuracy of the natural frequencies for the significant first and second modes of vibration via pole-zero estimation strategy. Meanwhile, to validate the accuracy of the model compared to the actual system, correlation tests are applied. The comparisons of ABC and FFA performances in system identification are highlighted in this paper. The results reveal that ABC has the superior advantage over FFA in developing an 8th order system which yields minimum MSE of 5.5786×10-12, accurate natural frequencies simultaneously correlates within 95% of the confidence interval.

Periodic, quasiperiodic, fractal, Kolakoski, and random binary polymers: Energy structure and carrier transport.

We study periodic, quasiperiodic (Thue-Morse, Fibonacci, period doubling, Rudin-Shapiro), fractal (Cantor, generalized Cantor), Kolakoski, and random binary sequences using a tight-binding wire model, where a site is a monomer (e.g., in DNA, a base pair). We use B-DNA as our prototype system. All sequences have purines, guanine (G) or adenine (A), on the same strand, i.e., our prototype binary alphabet is {G,A}. Our aim is to examine the influence of sequence intricacy and magnitude of parameters on energy structure, localization, and charge transport. We study quantities such as autocorrelation function, eigenspectra, density of states, Lyapunov exponents, transmission coefficients, and current-voltage curves. We show that the degree of sequence intricacy and the presence of correlations decisively affect the aforementioned physical properties. Periodic segments have enhanced transport properties. Specifically, in homogeneous sequences transport efficiency is maximum. There are several deterministic aperiodic sequences that can support significant currents, depending on the Fermi level of the leads. Random sequences is the less efficient category.

Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements

This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR.