Performance Of Digital Systems Research Articles

A Digital WATERMARKING Algorithm with High Efficiency Based on DWT and LSB

In order to improve the performance of digital watermarking system, a novel watermarking algorithm for blind watermarking based on the least significant bits and support vector machine. Firstly, digital watermarking was pretreated by binaryzation. Subsequently, the watermark signal is embedded into least significant bit of the low frequency coefficients by the Discrete Wavelet Transformation. Finally, the trained support vector machine is used to extract the attacking vetors. Simulation results show that the watermarking algorithm has good invisibility and robustness to general attacks and geometrical distortions.

Characterization of a Gm-C Filter Based on CNTFETs for Use in Digital Audio Broadcasting Systems

Anti-aliasing filters play an important role in analog front-end circuits, and their suitable design can improve the performance of digital audio broadcasting systems. In this paper, a Gm-C anti-aliasing filter based on carbon nanotube field effect transistors (CNTFETs) is proposed. Using CNTFETs provides low power consumption and appropriate frequency response. Simulation results show that these characteristics are widely dependent on the physical parameters of CNTFETs. The effects of chirality, the number of CNTs in each CNTFET, and distance of CNTs from each other on power consumption and frequency response are investigated. Among these parameters, the chirality and number of CNTs respectively have nonlinear and linear relationships with both power consumption and cutoff frequency. On the other hand, changing the distance between CNTs has the least effect on the output characteristics. Also, the output features of the filter for different gate oxides and channel lengths are studied. The overall result of the simulations demonstrates that the filters based on CNTFETs are promising candidates to be used in future nano-scale integrated circuits.

Counteracting the Dynamical Degradation of Digital Chaos by Applying Stochastic Jump of Chaotic Orbits

The performance of digital chaotic systems in secure communications and cryptographic applications is significantly degraded due to the limited precision of digital computational devices that are used to implement digital chaotic systems. However, regardless of the initial value, the digital chaotic map employed in these applications converges to several periodic orbits. Thus, a periodic orbit search algorithm (POSA) can be designed to accurately locate fixed points and limit cycles. In addition, an effective method based on stochastic jumps of chaotic orbits is proposed to counteract the performance degradation of digital chaos. Numerical simulations were performed to assess the effectiveness and feasibility of the proposed method in terms of autocorrelation, phase space inspection, approximate entropy and periodicity analysis. Furthermore, comparison with other existing methods is presented to show the competitiveness of the proposed scheme. Finally, a pseudorandom bit generator (PRBG), with desirable statistical properties, is constructed for chaos cryptography and other applications.

On the Performance of $\alpha$ –$\eta$ –$\kappa$ –$\mu$ Fading Channels

In this letter, we study the performance of digital communication systems considering the general and versatile α-η-κ-μ fading model, which was recently proposed in the literature. To this end, novel and exact expressions for the outage probability, average channel capacity, and average error rate of a variety of modulation formats are derived for arbitrary values of the fading parameters. Moreover, an asymptotic outage analysis is carried out in order to get further insight as to how the fading parameters impact system performance. Monte Carlo simulations are provided to validate the proposed analytical framework.

Performance evaluation of an ultra-high speed adder based on quantum-dot cellular automata

Quantum-dot cellular automata (QCA) is among the most promising nanotechnologies as the substitution for the current metal oxide semiconductor field effect transistor based devices. Therefore, lots of attention have been paid to different aspects to improve the efficiency of QCA circuits. In this way, the adder circuits are widely investigated since their performance can directly affect the whole digital system performance. In this paper, a new ultra-high speed QCA full adder cell is proposed based on multi-layer structures. The proposed full adder cell is simple in design using 3-input Exclusive-OR (TIEO), which computes the Sum bits and Majority gate, which computes the Carry bits. To verify the efficacy of the presented full adder cell, it is considered, the main constructing block in 4-bit ripple carry adder circuit. Hence, significant improvements in terms of area and cell count have been achieved. Particularly simulation results show 20% and 1.8% reduction respectively in the area and cell count overhead. Detailed performance evaluation and structural analysis are performed in different aspects to authenticate the proposed circuits (one-bit and 4-bit) having superb performance in comparison to previously reported works. QCADesigner CAD tool has been used to verify the correct functionality of the proposed architectures.

A study of multi-angles knife-edge method applied to digital modulation transfer function measurement

The objective of this study was to propose a newly-developed method to calculate digital modulation transfer function (DMTF) of digital image system which integrates with CCD/CMOS, non-linearity response and modulation transfer function (MTF) of optics, and is supposed to be linear response. According to previous studies, an imager in terms of its optical transfer function is not appropriate for a discrete imaging system when aliasing occurs, since these optical systems transform high spatial frequencies into low frequencies; the measure of how efficient micro-scanning method could remove the aliasing effects from various assigned optics. In this research, multiple angle knife edge as light sources are employed in this measurement to find out the pristine performance of digital image system. After a comprehensive analysis on the results of the above MTF, it was established that a quick and effective DMTF measurement system was developed to evaluate the pristine performance of digital cameras.

Performance Analysis of Digital Communication Systems Over $\alpha$ -$\kappa$ -$\mu$ Fading Channels

In this letter, the performance of digital communications systems over $\alpha $ - $\kappa $ - $\mu $ fading channels is analyzed in terms of outage probability, average channel capacity, and average error rate for a variety of modulation formats. To this end, novel and exact expressions for the aforementioned performance metrics are derived, based on which an asymptotic analysis is carried out. The derived expressions are valid for arbitrary values of the fading parameters, namely $\alpha $ , $\kappa $ , and $\mu $ , and their accuracies are validated through Monte Carlo simulations.

WAVELET METHODS FOR CARDIO SIGNALS PROCESSING

The article discusses the use of wavelet transforms and algorithms in the digital processing of cardiosignals in a number of medical applications due to their good adaptability to the analysis of non-stationary signals (that is, those whose statistical characteristics change with time). Since an electrocardiogram is a transient signal, wavelet methods can be used to recognize and detect key diagnostic features. In real-time systems for digital signal processing, it is important that mathematical operations are performed quickly, and the time required to execute commands must be known precisely and in advance. For this, both the program and the hardware must be very effective. In digital signal processors, the most important mathematical operation and the core of all digital signal processing algorithms is multiplication, followed by summation. Fast execution of the multiplication operation followed by summation is very important for implementing real-time digital filters, signal processing, matrix multiplication, and graphic image manipulation. Therefore, all this requires the need to improve methods, algorithms and signal processing programs that determine the quality and performance of digital systems. The technique is based on the transformation of the heart rate to simple harmonic oscillations (fast Fourier transform, autoregressive analysis) with different frequencies. In this case, the sequence of heartbeats is converted into a power spectrum of fluctuations of the duration of the RR intervals, which are a sequence of frequencies characterizing HRV. Most often, the area bounded by the spectral power curve corresponding to a certain defined frequency range, that is, the power within a limited frequency range, is estimated.

Clinical performance of digital mammography systems in a breast screening programme – An update

The purpose of this research was to compare the clinical performance of three individual digital mammography (DM) systems utilised within a population based screening program. The results presented here expand on previously published data from a 3 to a 9 year period. 28 DM systems from three different vendors were involved in the study. The retrospective analysis included 971612 screening examinations of females aged between 50 and 64 years. All images were double read and assigned a result according to a 5 point rating scale to indicate the probability of cancer. Women with a positive result were recalled for further assessment imaging and biopsy if necessary. Clinical performance in terms of cancer detection rate was analysed and the results presented A total of 5262 cancers were diagnosed. No statistically significant difference was found between the three individual mammography systems in terms of overall cancer detection rate or in the detection of invasive cancer and ductal carcinoma in situ. This was shown in both prevalent and subsequent screening examination categories. The results demonstrate comparable cancer detection performance for the three imaging system types. The study expansion from a 3 to a 9 year period provided sufficient numbers of cancers, 5262 (n = 971612) compared to 1632 (n = 238182) in the original study, to prove statistical significance. Overall the results provide a reassuring audit measure, suggesting that technical differences evident from routine quality assurance measurements do not appear to be reflected clinically in terms of overall cancer detection.

Downlink LTE System Performance Improvement by Using BCH Codes over LTE-MIMO Channel

Long-term Evolution (LTE) has potential feasibility to implement high-speed data transmission. This technology is essential for accommodating the rising utilization of data and voice service. Nonetheless, the main problem is the deteriorated performance of wireless communication systems following the elevation in bit error rate (BER) owing to multipath fading environments. Therefore, using channel coding is essential to reduce BER, which leads to enhancement of system performance of digital communication systems. Previous studies have reported utilization of channel codes including turbo and convolutional codes in LTE systems for attaining error control system. As such, the key challenge of selecting category of coding method is the trade-off between elevating decoding complexity and enhancing system performance. Hence, the study herein proposed Bose and Chaudhuri (BCH) codes as channel coding for downlink LTE system over MIMO channel. This is aimed to attain an adaptive error control with low complexity compared to turbo and convolutional codes. The findings indicated that BCH codes had reduced BER compared to turbo and convolutional codes in both quadrature phase-shift keying (QPSK) modulation schemes and binary phase-shift keying (BPSK) with regard to the downlink LTE system performance. The suggested method had approximately 4dB coding gain at 1X10-1 against both of convolutional and turbo codes in BPSK. While, for QPSK, the proposed method had approximately 5dB and 6dB compared to turbo and convolutional codes, respectively. Nonetheless, enhanced performance of the suggested system was observed through reducing BER of the received data by adding the number of antennas in MIMO channel.

Neural network method for lossless two-conductor transmission line equations based on the IELM algorithm

With the increasing demands for vast amounts of data and high-speed signal transmission, the use of multi-conductor transmission lines is becoming more common. The impact of transmission lines on signal transmission is thus a key issue affecting the performance of high-speed digital systems. To solve the problem of lossless two-conductor transmission line equations (LTTLEs), a neural network model and algorithm are explored in this paper. By selecting the product of two triangular basis functions as the activation function of hidden layer neurons, we can guarantee the separation of time, space, and phase orthogonality. By adding the initial condition to the neural network, an improved extreme learning machine (IELM) algorithm for solving the network weight is obtained. This is different to the traditional method for converting the initial condition into the iterative constraint condition. Calculation software for solving the LTTLEs based on the IELM algorithm is developed. Numerical experiments show that the results are consistent with those of the traditional method. The proposed neural network algorithm can find the terminal voltage of the transmission line and also the voltage of any observation point. It is possible to calculate the value at any given point by using the neural network model to solve the transmission line equation.

Automated daily quality control analysis for mammography in a multi-unit imaging center.

The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

New Results on the Fluctuating Two-Ray Model With Arbitrary Fading Parameters and Its Applications

The fluctuating two-ray (FTR) fading model provides a much better fit than other fading models for small-scale fading measurements in millimeter wave communications. In this paper, using a mixture of gamma distributions, new exact analytical expressions for the probability density and cumulative distribution functions of the FTR distribution with arbitrary fading parameters are presented. Moreover, the performance of digital communication systems over the FTR fading channel is evaluated in terms of the channel capacity and the bit error rate. The interaction between channel fading parameters and system performance is further investigated. Our newly derived results extend and complement previous knowledge of the FTR fading model.

Black box model-based self healing solution for stuck-at-faults in combinational circuits

The paper unveils a black box model-based self healing strategy to suppress the ill effects of stuck-at-faults occurring in combinational circuits. The primary theory endeavours to attach a sense of reliability in the performance of digital systems and makes them insensitive to the negative impact of faults present in the system. The proposed methodology employs a dynamic fault tolerant approach to protect digital systems from the incursion of stuck-at-faults and enables the system to come up with fault free outputs. The simulation results affirm the authenticity of the proposed strategy to cancel out the influence of faults and facilitate the system to heal itself. The work utilizes the attributes of an FPGA to demonstrate the practical viability of the proposed approach. The performance analysis endorses the definite dominance of the proposed healing scheme over the traditional Triple Modular Redundancy [TMR] in terms of fault coverage and area overhead.

Design of novel QCA-based half/full subtractors

Quantum-dot cellular automata (QCA) is an emerging nanotechnology and a possible alternative to the related issues of traditional complementary metal oxide semiconductors. It offers advantages such as high device density, high operating speed and ultra-low power consumption compared with semiconductor transistor-based technologies. Adder and subtractor circuits are the fundamental arithmetic logic circuits used in digital systems. The performance of digital systems can directly affect the operation of adder and subtractor circuits. In this direction, several QCA digital approaches have been devised to increase the performance of adder and subtractor circuits. In this paper, novel half/full subtractors using a single-layer scheme of QCA cells are proposed. The proposed structures have the most beneficial features of low power consumption, reduced area, less latency (clock delays) and circuit complexity (number of cells) compared to conventional designs. In addition, a novel controlled half adder/subtractor is presented. The modular layouts are verified with the freely available QCADesigner tool version 2.0.3. The results of computer simulations carried out on the proposed designs have confirmed the suitability of the proposed techniques.

Locally Optimal Inspired Detection in Snapping Shrimp Noise

In this paper, we address the problem of detecting a known signal in snapping shrimp noise. The latter dominates the ambient soundscape at medium-to-high frequencies in warm shallow waters. The noise process is impulsive, exhibits memory and is modeled effectively by stationary α-sub-Gaussian noise with memory order m (αSGN(m)), which is essentially an impulsive Markov process. Robust detectors have long been used to mitigate the impact of impulsive noise on the performance of digital systems. However, conventional notions of robustness do not assume memory within the noise process. The αSGN(m) model offers a mathematical model to develop robust detectors that also exploit the mutual information between noise samples. Recent works in this area highlight substantial improvement in detection performance over traditional robust methods in snapping shrimp noise. However, implementing such detectors is a challenge as they are parametric and computationally taxing. To achieve more realizable detectors, we derive the locally optimal detector for αSGN(m). From it, we introduce the generalized memory-based sign correlator and its variants, all of which offer near-optimal performance in αSGN(m). The proposed detectors offer excellent performance in snapping shrimp noise and low computational complexity. These properties make them attractive for use in underwater acoustical systems operating in snapping shrimp noise.

Classification of Error Correcting Codes and Estimation of Interleaver Parameters in a Noisy Transmission Environment

Channel encoder, which includes a forward error correcting (FEC) code followed by an interleaver, plays a vital role in improving the error performance of digital storage and communication systems. In most of the applications, the FEC code and interleaver parameters are known at the receiver to decode and de-interleave the information bits, respectively. But the blind/semi-blind estimation of code and interleaver parameters at the receiver will provide additional advantages in applications, such as adaptive modulation and coding, cognitive radio, non-cooperative systems, etc. The algorithms for the blind estimation of code parameters at the receiver had previously been proposed and investigated for known FEC codes. In this paper, we propose algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder. The proposed algorithm classify the incoming data symbols among block coded, convolutional coded, and uncoded symbols. Further, we suggest analytical and histogram approaches for setting the threshold value to perform code classification and parameter estimation. It is observed from the simulation results that the code classification and interleaver parameter estimation are performed successfully over erroneous channel conditions. The proposed histogram approach is more robust against the analytical approach for noisy transmission environment and system latency is one of the important challenges for the histogram approach to achieve better performance.

Design and implementation of a container-based virtual client architecture for interactive digital signage systems

Interactive digital signage is an important Internet of things application and has been becoming a common type of human–machine interface for multiple users. By integrating with wireless sensor networks, a digital signage system can provide smart features and on-demand contents to users. However, the performance of current interactive digital signage systems depends heavily on the server. An increasingly high number of digital signage clients and sensor devices attached to the system generating a huge amount of traffic flowed to the server may create bottleneck, management and scalability issues at the server, especially in large-scale digital signage systems. In addition, the current system requires application installation and configuration at the client side, thus leading to a high cost and complexity of deployment as well as management. This article proposes and implements a container-based distributed virtual client architecture for interactive digital signage to solve the above issues. In the proposed architecture, a number of digital signage clients and Internet of things devices are virtualized and managed by a container-based middleware. Each container-based middleware is responsible to manage and process data for a cluster of digital signage clients and corresponding Internet of things devices to (1) reduce load to server and improve the service performance and (2) enable lightweight clients to reduce cost and complexity in deployment as well as management. Implementation and obtained analysis results show the advantages of the proposed architecture.

Some alternative derivations of Craig's formula

In the performance of digital communication systems over fading channels, the error analysis is typically modelled using a Gaussian probability distribution. One function central to the analysis is what engineers routinely refer to as the (Gaussian) Q-function and is defined by1This is the canonical representation used for the function. In this paper a number of derivations of an important alternative representation for the Q-function known as Craig's formula will be given.

Experimental investigation on operating performance of digital variable multiple air conditioning system

The objective of this paper was to study operating performance of digital variable multiple (DVM) air conditioning (AC) system by experiments. Variable refrigerant flow performance, part load performance, defrosting performance, and energy consumption model of DVM AC system were analyzed by experimental data. The results indicate that variable refrigerant volume characteristic and excellent part load performance are beneficial to seasonal energy saving operation of DVM AC system. Seasonal energy consumption of DVM AC system is able to be calculated based on hourly energy consumption model and defrosting energy consumption model obtained by experimental data regression. Under defrosting condition, indoor unit which contributes the most to defrosting is the one nearest to outdoor unit and its corresponding indoor thermal environment is adversely affected. Thus, it is suggested to take this factor into account when configuring the capacity of the indoor unit which is nearest to outdoor unit.