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Chapter and Conference Paper
Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network
Content-based image retrieval CBIR is a technique that helps in searching a user desired information from a huge set of image files and interpret user intentions for the desired information. The retrieval of i...
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Article
Open AccessA simple approach to evaluate the ergodic capacity and outage probability of correlated Rayleigh diversity channels with unequal signal-to-noise ratios
In this article, we propose a novel method to derive exact closed-form ergodic capacity and outage probability expressions for correlated Rayleigh fading channels with receive diversity. Unlike the existing wo...
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Article
A Unified Performance Analysis of the Family of Normalized Least Mean Algorithms
This work presents a unified performance analysis of the family of normalized least mean (NLM) algorithms under very weak assumptions. The key feature of the analysis is based on a recently proposed performanc...
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Article
Open AccessFamily of state space least mean power of two-based algorithms
In this work, a novel family of state space adaptive algorithms is introduced. The proposed family of algorithms is derived based on stochastic gradient approach with a generalized least mean cost function J[k]=E
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Article
State Space Least Mean Fourth Algorithm for Dynamic State Estimation in Power Systems
Power system dynamic state estimation (DSE) has always been a critical problem in studying power systems. One of the essential parts of power systems are synchronous machines. In this work, we dealt with the p...
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Article
Open AccessMultiple access interference in MIMO-CDMA systems under Rayleigh fading: statistical characterization and applications
A major limiting factor in the performance of multiple-input-multiple-output (MIMO) code division multiple access (CDMA) systems is multiple access interference (MAI) which can reduce the system’s capacity and...
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Article
Differences in photosynthetic syndromes of four halophytic marsh grasses in Pakistan
Salt-tolerant grasses of warm sub-tropical ecosystems differ in their distribution patterns with respect to salinity and moisture regimes. Experiments were conducted on CO2 fixation and light harvesting processes...
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Article
A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks
In this research, we propose a novel algorithm for learning of the recurrent neural networks called as the fractional back-propagation through time (FBPTT). Considering the potential of the fractional calculus...
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Article
q-State Space Least Mean Family of Algorithms
It is generally known that model-based estimation algorithms (such as Kalman filter and its family) perform better than the non-model-based algorithms [such as least mean square (LMS), recursive least squares]...
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Article
Does a one-size-fits-all approach to financial regulations alleviate default risk? The case of dual banking systems
Financial regulations are developed to curb financial and economic fragility costs without undermining the economic contributions of banks to economic development. To understand the impact financial regulation...
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Article
Sum Ergodic Capacity Analysis Using Asymptotic Design of Massive MU-MIMO Systems
This communication attempts to characterize the performance metrics of downlink Massive MU-MIMO systems impaired by cochannel interference and additive noise over a Rayleigh fading environment. We obtain close...
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Article
On the Kernel Optimization of Radial Basis Function Using Nelder Mead Simplex
Artificial neural networks in general and radial basis function in particular are known for high accuracies in function approximation, nonlinear system identification, and pattern classification problems; howe...
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Article
A State-Space Backpropagation Algorithm for Nonlinear Estimation
The fact that the knowledge of system model enhances the performance of any estimation algorithm is well known. However, the existing state-space-based algorithms are either linear such as the Kalman Filter an...
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Article
Improved Optimum Error Nonlinearities Using Cramer–Rao Bound Estimation
In this paper, we propose an efficient design of optimum error nonlinearities (OENL) for adaptive filters which minimizes the steady-state excess mean square error and attains the limit mandated by the Cramer–...
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Chapter and Conference Paper
q-LMF: Quantum Calculus-Based Least Mean Fourth Algorithm
Herein, we a new class of stochastic gradient algorithm for identification. The proposed q-least mean fourth (q-LMF) is extension of the least mean fourth (LMF) and it is based on the q-calculus which is ...
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Article
System reliability analysis of small-cell deployment in heterogeneous cellular networks
This paper exhibits a primer on the use of modern system reliability techniques on several important topologies of small-cell deployment in multi-tier dense cellular networks. We synthesize a network into seve...
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Article
Comments on “Design of fractional-order variants of complex LMS and NLMS algorithms for adaptive channel equalization”
The purpose of this note is to discuss some aspects of recently proposed fractional-order variants of complex least mean square (CLMS) and normalized least mean square (NLMS) algorithms in Shah et al. (Nonline...
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Article
Diffusion Quantum-Least Mean Square Algorithm with Steady-State Analysis
Diffusion least mean square (LMS) algorithm is a well-known algorithm for distributed estimation where estimation takes place at multiple nodes. However, it inherits slow convergence speed due to its gradient ...
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Article
Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links
The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. Motivated by this fact, a quantum calculus-based noisy links incremental least mean square...
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Article
An efficient normalized LMS algorithm
The task of adaptive estimation in the presence of random and highly nonlinear environment such as wireless channel estimation and identification of non-stationary system etc. has been always challenging. The ...