نتایج جستجو برای: hopfield

تعداد نتایج: 1925  

2012
Hazem M. El-Bakry

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR sig...

2008
Hazem M. El-Bakry Nikos Mastorakis

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR sig...

Journal: :Intelligent Automation & Soft Computing 2012
Emad Issa Abdul Kareem Wafaa A. H. Ali Alsalihy Aman Jantan

Although Hopfield neural network is one of the most commonly used neural network models for auto-association and optimization tasks, it has several limitations. For example, it is well known that Hopfield neural networks has limited stored patterns, local minimum problems, limited noise ratio, retrieve reverse value of pattern, and shifting and scaling problems. This research will propose multi...

2011
Emad I Abdul Kareem Aman Jantan

Although Hopfield neural network is one of the most commonly used neural network models for auto-association and optimization tasks, it has several limitations. For example, it is well known that Hopfield neural networks has limited stored patterns, local minimum problems, limited noise ratio, retrieve reverse value of pattern, and shifting and scaling problems. This research will propose multi...

دژکام, رسول , شاهمیری, امیرشهاب , صفابخش, رضا صفابخش,

Automatic correction of typos in the typed texts is one of the goals of research in artificial intelligence, data mining and natural language processing. Most of the existing methods are based on searching in dictionaries and determining the similarity of the dictionary entries and the given word. This paper presents the design, implementation, and evaluation of a Farsi typo correction system u...

2006
Vo Ngoc Dieu Weerakorn Ongsakul

This paper proposes a simple enhanced augmented Hopfield Lagrange neural network (EALH) for solving economic dispatch (ED) problem with piecewise quadratic cost functions. The EALH is an augmented Lagrange Hopfield neural network (ALH), which is a combination of continuous Hopfield neural network and augmented Lagrangian relaxation function as its energy function, enhanced by a heuristic search...

2016
Marius-F. Danca Avram Iancu Nikolay Kuznetsov

In this letter we unveil the existence of transient hidden coexisting chaotic attractors, in a simplified Hopfield neural network with three neurons. keyword Hopfield neural network; Transient hidden chaotic attractor; Limit cycle

2009
Zekeriya Uykan

Continuous-time Hopfield network has been an important focus of research area since 1980s whose applications vary from image restoration to combinatorial optimization from control engineering to associative memory systems. On the other hand, in wireless communications systems literature, power control has been intensively studied as an essential mechanism for increasing the system performance. ...

2004
F. Taylor G. Papadourakis A. Skavantzos

The effect of noise degradation on the Hopfield neural netwerk is s t u d i e d The notion of a hysteresis nefwork is defined. A noisy HephsSi =urd network is subsequently proven to be a hysteresis network. The effect of the hysteresis phentmenon on the robustness of the HoppeM neural network to noise degradation is then investigated. An eptiraal Heefield neural network is defined as the Hopfie...

2013
Amit Singh Somesh Kumar T. P. Singh

The combination of evolutionary algorithms and ANN has been a recent interest in the field of research. Hopfield model is a type of recurrent neural network which has been widely studied for the purpose of associative memories. In the present work, this Hopfield Model of feedback neural networks has been studied with Monte Carlo adaptation learning rule and one evolutionary searching algorithm ...

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