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Uniformly distributed pseudo-random number generators are commonly used in certain numerical algorithms and simulations. In this article a random number generation algorithm based on the geometric properties of complex Horadam sequences was investigated. For certain parameters, the sequence exhibited uniformity in the distribution of arguments. This feature was exploited to design a pseudo-random...
This paper presents the results of an exploratory research study that investigates factors contributing to preference for the agile software development approaches. The initial exploration revolves around the Five Factor Model of personality and the premise that these personality factors provide a partial explanation of preference for an agile approach. A survey instrument for measuring the preference...
We deliver a design flow for the synthesis and convergence of application-specific networks-on-chip. The flow comes with novel features that can better address nanoscale design challenges: front-end driven floorplanning, dynamic IR-drop minimization, fast and accurate system-level power grid modeling, predictable link design. Above all, such features are addressed by different prototype engines, even...
Equalizer is widely applied in communication systems to eliminate Inter-Symbol Interference mainly caused by multipath over wireless channels. Various algorithms are developed for coefficients update of the equalizer when tracking the channel. However, advantages and drawbacks coexist for single updating algorithm. In this paper, instead of single algorithm applied in the whole frame, two algorithms,...
Signal and image reconstruction from Fourier Transform magnitude is a difficult inverse problem. Fourier transform magnitude can be measured in many practical applications, but the phase may not be measured. Since the autocorrelation of an image or a signal can be expressed as convolution of x(n) with x(−n), it is possible to formulate the inverse problem as a non-negative matrix factorization problem...
We propose a blind correction approach to eliminate the distortion imported by timing skew, gain and offset mismatches in time-interleaved analog to digital converters (TIADC). The approach works in digital domain which can be used in M-channel TIADC. The correction algorithm for timing skew mismatch is based on synthesis filter banks and the estimation algorithm uses the crosscorrelation of adjacent...
The development of fast MPPT (Maximum Power Point Tracking) algorithms for photovoltaic (PV) systems able to track variable irradiation conditions with high bandwidth is becoming attractive, especially for mobile applications. This paper focuses on the well known ripple correlation technique, proposing an analysis that provides an upper bound to the convergence time in response to solar irradiation...
In this work, an adaptive method for estimating blind MMSE equalizer with arbitrary delay of SIMO channel is proposed. By using an RLS-similar algorithm to recursively update correlation matrix and its pseudo inverse, the proposed algorithm ensures convergence and is not sensitive to initialization. Compared with other batch-type approaches, the new adaptive method doesn't require directly computing...
In this paper we develop an intelligent algorithm that obtains the optimal trajectory (i.e., a non equally spaced sequence of stopping points) for a robot which tries to find a wireless channel with a minimum predefined channel gain over which to transmit its data. We show that this algorithm can be optimized in two ways: (i) minimum searching time (but suboptimal energy expenditure), or (ii) minimum...
This paper presents modified artificial fish swarm algorithm (MAFSA) for automated design and optimization of self-organizing fuzzy logic controller (SOFLC). MAFSA has main improvement in the information of global best AF which is added to the behaviours of AF. It is proposed a novel method of adaptive step and visual based on food concentration. These improvements not only increase the capability...
We examine patterns of evaluation on the open peer review forum of the AltCHI panel of the ACM SIGCHI Conference on Human Factors in Computing Systems, 2012–2013. By analyzing a dataset including all available reviews posted on the AltCHI online platforms, we find that author reviewers are more critical than external commentators, and later submission reviews are more favorable than earlier ones....
In many randomized consensus algorithms, the constraint of average preservation may not be enforced at every time step, resulting in an error between the average of the initial conditions and the current average. We have recently shown that under mild conditions on the distribution of the update matrices, the mean square error has an upper bound inversely proportional to the size of the network. In...
The convergence analysis of an online system identification method based on binary-quantized observations is presented in this paper. This recursive algorithm can be applied in the case of finite impulse response (FIR) systems and exhibits low computational complexity as well as low storage requirement. This method, whose practical requirement is a simple 1-bit quantizer, implies low power consumption...
In this paper, using observed data, the characteristics of two different feature of one heavy snowfall in North China region from 25 to 27 February, 2011 are studied. Results show that the heavy snowfall can be divided into two stages. The snowfall happened in same background circulation, but showed two different characteristics. First, the affecting systems of two stages of snowfall are different:...
Data collection, data processing, and imaging in exploration seismology increasingly hinge on large-scale sparsity promoting solvers to remove artifacts caused by efforts to reduce costs. We show how the inclusion of a “message term” in the calculation of the residuals improves the convergence of these iterative solvers by breaking correlations that develop between the model iterate and the linear...
A novel variable step size constant modulus algorithm (VSS-CMA) employing cross correlation between channel output and error signal has been proposed as a solution to the problem of slow convergence of CMA algorithm. The new algorithm resolves the conflict between the convergence rate and low steady state error of the fixed step-size conventional CMA algorithm. Computer simulations have been performed...
This paper presents an overview of sliding-window based learning with data store management (DSM) techniques using multilayer perceptron (MLP) neural network. The paper views several DSM techniques used to reduce the correlation of data inside the window store. The sliding window (SW) training is a form of higher order instantaneous learning strategy without the need of covariance matrix, usually...
In this work we investigate the best possible convergence of average consensus in the mean-square sense with weights that change over time. Although this convergence may be hard to achieve in practice, it provides useful practical insights into the behavior of average consensus. In particular, we show that the correlation between the states plays an important role in the design of the weights and...
This paper investigates convergence in diversity gain of multi-port antennas in non-rich multipath environments. It is shown that diversity gain convergence is faster in the presence of strong coupling. In this situation, richness threshold is also smaller. Furthermore, by linking convergence in diversity gain to convergence in antenna ports' correlations, the role of pattern diversity caused by coupling...
In this paper, a new efficient adaptive filtering algorithm belonging to the Quasi-Newton (QN) family is proposed. In the new algorithm, the autocorrelation matrix is assumed to be Toeplitz. Due to this assumption, the algorithm can be implemented in the frequency domain using the fast Fourier transform (FFT). The proposed algorithm turns out to be particularly suitable for adaptive channel equalization...
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