ITERATIVE APPROXIMATION OF FIXED POINTS OF (ASYMPTOTICALLY) NONEXPANSIVE MAPPINGS

Let E be a uniformly convex Banach space which satisfies Opial's condition or has a Frechet differentiable norm,and C be a bounded closed convex subset of E. If T∶C→C is (asymptotically)nonexpansive,then the modified Ishikawa iteration process defined byx n+1 =t nT ns nT nx n+1-s nx n+(1-t n)x n,converges weakly to a fixed point of T ,where {t n} and {s n} are sequences in [0,1] with some restrictions.

ISHIKAWA ITERATIVE PROCEDURE FOR APPROXIMATING FIXED POINTS OF STRICTLY PSEUDOCONTRACTIVE MAPPINGS

It is shown that any fixed point of a Lipschitzian,strictly pseudocontractive muping T on a closed convex subset K of a Banach space X may be approximated by Ishikawa iterative procedure.The results in this paper provide the new convergence criteria and novel convergence rate estimate for Ishikawa iterative sequence.

CONVERGENT PROBLEM OF ITERATIVE SEQUENCES FOR NONLINEAR MAPPINGS WITH ERROR MEMBERS IN BANACH SPACES

In this paper,the approximation problems of Ishikawa iteration with errors of fixed points for asymptotically nonexpansive mappings and asymptotically pseudocontractive mappings in arbitrary real Banach spaces are investigated.Some necessary condition and sufficient condition for the convergence of iterative sequences are given respectively.The results thus extend and improve some recent corresponding results.

CONVERGENCE RATE ESTIMATE OF ISHIKAWA ITERATIVE SEQUENCE FOR STRICTLY PSEUDOCONTRACTIVE MAPPINGS

Itis shown that any fixed point of each Lipschitzian,strictly pseudocontractive map- ping T on a closed convex subset K of a Banach space X may be norm approximated by Ishikawa iterative procedure.The argument in this paper provides a convergence rate estimate. Moreover the resultin this paper improves,generalizes and summarizes some important and el- egant recent results

A Chaotic Pulse Train Generator Based on Henon Map

The Henon map forms one of the most-studied two-dimensional discrete-time dynamical systems that exhibits chaotic behavior.The Henon map takes a point(Xn,Yn)in the plane and maps it to a new point(Xn+1,Yn+1).In this paper,a chaotic pulse generator based on the chaotic Henon map is proposed.It consists of a Henon map function subcircuit to realize the Henon map and another subcircuit to perform the iterative operation.The Henon map subcircuit comprises operational amplifiers,multipliers,delay elements and resistors,whereas,the iterative subcircuit is implemented with a simple design that comprises of an edge forming circuit followed by a monostable multivibrator and a voltage controlled switch without the use of any clock control.The proposed design can be used to realize the Henon map and also to generate a chaotic pulse train,with a controllable time interval and pulse position.The proposed circuit is implemented and simulated using Multisim 13.0 and MATLAB R2019b.The chaotic nature of the generated pulse train and also the time interval between the consecutive pulses is verified by the calculation of its Lyapunov exponents.

Mode shift and stability control of a current mode controlled buck-boost converter operating in discontinuous conduction mode with ramp compensation

By establishing the discrete iterative mapping model of a current mode controlled buck-boost converter, this paper studies the mechanism of mode shift and stability control of the buck-boost converter operating in discontinuous conduction mode with a ramp compensation current. With the bifurcation diagrazn, Lyapunov exponent spectrum, time- domain waveform and parameter space map, the performance of the buck-boost converter circuit utilizing a compensating ramp current has been analysed. The obtained results indicate that the system trajectory is weakly chaotic and strongly intermittent under discontinuous conduction mode. By using ramp compensation, the buck-boost converter can shift from discontinuous conduction mode to continuous conduction mode, and effectively operates in the stable period-one region.

Dynamical analysis and experimental verification of valley current controlled buck converter

The dynamical behaviours of valley current controlled buck converter are studied by establishing its corresponding discrete iterative map model in this paper. Time-domain waveforms and phase portraits of valley current controlled buck converter are obtained by Runge-Kutta algorithm through a piecewise smooth switching model. The research results indicate that the valley current controlled buck converter exhibits rich nonlinear phenomena, and it has routes to chaos through period-doubling bifurcation and border-collision bifurcation in a wide parameter range. Interesting inverse nonlinear behaviours compared with peak current controlled buck converter are observed in the valley current controlled buck converter. Analysis and simulation results are verified by experimental results.

Dynamics and stabilization of peak current-mode controlled buck converter with constant current load

The discrete iterative map model of peak current-mode controlled buck converter with constant current load（CCL）,containing the output voltage feedback and ramp compensation, is established in this paper. Based on this model the complex dynamics of this converter is investigated by analyzing bifurcation diagrams and the Lyapunov exponent spectrum. The effects of ramp compensation and output voltage feedback on the stability of the converter are investigated. Experimental results verify the simulation and theoretical analysis. The stability boundary and chaos boundary are obtained under the theoretical conditions of period-doubling bifurcation and border collision. It is found that there are four operation regions in the peak current-mode controlled buck converter with CCL due to period-doubling bifurcation and border-collision bifurcation. Research results indicate that ramp compensation can extend the stable operation range and transfer the operating mode, and output voltage feedback can eventually eliminate the coexisting fast-slow scale instability.

Symmetrical dynamics of peak current-mode and valley current-mode controlled switching dc-dc converters with ramp compensation

The discrete iterative map models of peak current-mode （PCM） and valley current-mode （VCM） controlled buck converters, boost converters, and buck-boost converters with ramp compensation are established and their dynamical behaviours are investigated by using the operation region, parameter space map, bifurcation diagram, and Lyapunov exponent spectrum. The research results indicate that ramp compensation extends the stable operation range of the PCM controlled switching dc-dc converter to D 〉 0.5 and that of the VCM controlled switching dc-dc converter to D 〈 0.5. Compared with PCM controlled switching dc-dc converters with ramp compensation, VCM controlled switching dc-dc converters with ramp compensation exhibit interesting symmetrical dynamics. Experimental results are given to verify the analysis results in this paper.

Ensemble Nonlinear Support Vector Machine Approach for Predicting Chronic Kidney Diseases

Urban living in large modern cities exerts considerable adverse effectson health and thus increases the risk of contracting several chronic kidney diseases (CKD). The prediction of CKDs has become a major task in urbanizedcountries. The primary objective of this work is to introduce and develop predictive analytics for predicting CKDs. However, prediction of huge samples isbecoming increasingly difficult. Meanwhile, MapReduce provides a feasible framework for programming predictive algorithms with map and reduce functions.The relatively simple programming interface helps solve problems in the scalability and efficiency of predictive learning algorithms. In the proposed work, theiterative weighted map reduce framework is introduced for the effective management of large dataset samples. A binary classification problem is formulated usingensemble nonlinear support vector machines and random forests. Thus, instead ofusing the normal linear combination of kernel activations, the proposed work creates nonlinear combinations of kernel activations in prototype examples. Furthermore, different descriptors are combined in an ensemble of deep support vectormachines, where the product rule is used to combine probability estimates ofdifferent classifiers. Performance is evaluated in terms of the prediction accuracyand interpretability of the model and the results.

Dynamical Behavior of V^2C Control Boost Converter

A discrete iterative map model of V^2C control boost converter was established to study the dynamical behaviors of the converter. By using parameter space map and bifurcation diagram, the effects of circuit parameters on the bifurcation behaviors of V^2C control and current-mode control boost converters were analyzed. The phase portraits and time-domain waveforms of the V^2C control boost converter were obtained by Runge-Kutta algorithm through piecewise smooth switching model. The research results indicate that V^2C control boost converters can evolve into periodic and chaotic behaviors, and show weaker nonlinear behaviors than current-mode control boost converters.

Balancing Exploration–Exploitation of Multi-verse Optimizer for Parameter Extraction on Photovoltaic Models

Extracting photovoltaic(PV)model parameters based on the measured voltage and current information is crucial in the simulation and management of PV systems.To accurately and reliably extract the unknown parameters of different PV models,this paper proposes an improved multi-verse optimizer that integrates an iterative chaos map and the Nelder–Mead simplex method,INMVO.Quantitative experiments verified that the proposed INMVO fueled by both mechanisms has more affluent populations and a more reasonable balance between exploration and exploitation.Further,to verify the feasibility and competitiveness of the proposal,this paper employed INMVO to extract the unknown parameters on single-diode,double-diode,three-diode,and PV module four well-known PV models,and the high-performance techniques are selected for comparison.In addition,the Wilcoxon signed-rank and Friedman tests were employed to test the experimental results statistically.Various evaluation metrics,such as root means square error,relative error,absolute error,and statistical test,demonstrate that the proposed INMVO works effectively and accurately to extract the unknown parameters on different PV models compared to other techniques.In addition,the capability of INMVO to stably and accurately extract unknown parameters was also verified on three commercial PV modules under different irradiance and temperatures.In conclusion,the proposal in this paper can be implemented as an advanced and reliable tool for extracting the unknown parameters of different PV models.Note that the source code of INMVO is available at https://github.com/woniuzuioupao/INMVO.