127 resultados para Binary Pll
Resumo:
Clock signal distribution in telecommunication commercial systems usually adopts a master-slave architecture, with a precise time basis generator as a master and phase-locked loops (PLLs) as slaves. In the majority of the networks, second-order PLLs are adopted due to their simplicity and stability. Nevertheless, in some applications better transient responses are necessary and, consequently, greater order PLLs need to be used, in spite of the possibility of bifurcations and chaotic attractors. Here a master-slave network with third-order PLLs is analyzed and conditions for the stability of the synchronous state are derived, providing design constraints for the node parameters, in order to guarantee stability and reachability of the synchronous state for the whole network. Numerical simulations are carried out in order to confirm the analytical results. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.
Resumo:
In many engineering applications, the time coordination of geographically separated events is of fundamental importance, as in digital telecommunications and integrated digital circuits. Mutually connected (MC) networks are very good candidates for some new types of application, such as wireless sensor networks. This paper presents a study on the behavior of MC networks of digital phase-locked loops (DPLLs). Analytical results are derived showing that, even for static networks without delays, different synchronous states may exist for the network. An upper bound for the number of such states is also presented. Numerical simulations are used to show the following results: (i) the synchronization precision in MC DPLLs networks; (ii) the existence of synchronous states for the network does not guarantee its achievement and (iii) different synchronous states may be achieved for different initial conditions. These results are important in the neural computation context. as in this case, each synchronous state may be associated to a different analog memory information. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The aim of this study was to determine whether inclusion complexes between 2-hydroxypropyl-beta-cyclodextrin (HP beta CD) and finasteride (FIN) are formed, and to characterize these. Equimolar FIN/HP beta CD solid systems in the presence or absence of 0.1% (w/v) of polyvinylpyrrolidone K30 (PVP K30) or 0.3% of chitosan were prepared by coevaporation and freeze-drying methods. The systems were characterized by phase solubility, NMR, DSC, and XRD analysis. The results suggest that true binary and ternary inclusion complexes were formed. (c) 2009 Elsevier Ltd. All rights reserved.
Resumo:
This study described the formulation and characterisation of the viscoelastic, mechanical and mucoadhesive properties of thermoresponsive, binary polymeric systems composed of poloxamer (P407) and poly(acrylic acid, C974P) that were designed for use as a drug delivery platform within the oral cavity. Monopolymeric and binary polymeric formulations were prepared containing 10, 15 and 20% (w/w) poloxamer (407) and 0.10-0.25% (w/w) poly(acrylic acid, 934P). The flow theological and viscoelastic properties of the formulations were determined using controlled stress and oscillatory rheometry, respectively, the latter as a function of temperature. The mechanical and mucoadhesive properties (namely the force required to break the bond between the formulation and a pre-hydrated mucin disc) were determined using compression and tensile analysis, respectively. Binary systems composed of 10% (w/w) P407 and C934P were elastoviscous, were easily deformed under stress and did not exhibit mucoadhesion. Formulations containing 15 or 20% (w/w) Pluronic P407 and C934P exhibited a sol-gel temperature T(sol/gel), were viscoelastic and offered high elasticity and resistance to deformation at 37 degrees C. Conversely these formulations were elastoviscous and easily deformed at temperatures below the sol-gel transition temperature. The sol-gel transition temperatures of systems containing 15% (w/w) P407 were unaffected by the presence of C934P; however, increasing the concentration of C934P decreased the T(sol/gel) in formulations containing 20%(w/w) P407. Rheological synergy between P407 and C934P at 37 degrees C was observed and was accredited to secondary interactions between these polymers, in addition to hydrophobic interactions between P407 micelles. Importantly, formulations composed of 20% (w/w) P407 and C934P exhibited pronounced mucoadhesive properties. The ease of administration (below the T(sol/gel)) in conjunction with the viscoelastic (notably high elasticity) and mucoadhesive properties (at body temperature) render the formulations composed of 20% (w/w) P407 and C934P as potentially useful platforms for mucoadhesive, controlled topical drug delivery within the oral cavity. (c) 2009 Published by Elsevier B.V.
Resumo:
Surface pressure (pi)-molecular area (A) curves were used to characterize the packing of pseudo-ternary mixed Langmuir monolayers of egg phosphatidylcholine (EPC), 1,2-dioleoyl-3-trimethylammonium propane (DOTAP) and L-alpha-dioleoyl phosphatidylethanolamine (DOPE). This pseudo-ternary mixture EPC/DOPE/DOTAP has been successfully employed in liposome formulations designed for DNA non-viral vectors. Pseudo-binary mixtures were also studied as a control. Miscibility behavior was inferred from pi-A curves applying the additivity rule by calculating the excess free energy of mixture (Delta G(Exc)). The interaction between the lipids was also deduced from the surface compressional modulus (C(s)(-1)). The deviation from ideality shows dependence on the lipid polar head type and monolayer composition. For lower DOPE concentrations, the forces are predominantly attractive. However, if the monolayer is DOPE rich, the DOTAP presence disturbs the PE-PE intermolecular interaction and the net interaction is then repulsive. The ternary monolayer EPC/DOPE/DOTAP presented itself in two configurations, modulated by the DOPE content, in a similar behavior to the DOPE/DOTAP monolayers. These results contribute to the understanding of the lipid interactions and packing in self-assembled systems associated with the in vitro and in vivo stability of liposomes. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
It is believed that eta Carinae is actually a massive binary system, with the wind-wind interaction responsible for the strong X-ray emission. Although the overall shape of the X-ray light curve can be explained by the high eccentricity of the binary orbit, other features like the asymmetry near periastron passage and the short quasi-periodic oscillations seen at those epochs have not yet been accounted for. In this paper we explain these features assuming that the rotation axis of eta Carinae is not perpendicular to the orbital plane of the binary system. As a consequence, the companion star will face eta Carinae on the orbital plane at different latitudes for different orbital phases and, since both the mass-loss rate and the wind velocity are latitude dependent, they would produce the observed asymmetries in the X-ray flux. We were able to reproduce the main features of the X-ray light curve assuming that the rotation axis of eta Carinae forms an angle of 29 degrees +/- 4 degrees with the axis of the binary orbit. We also explained the short quasi-periodic oscillations by assuming nutation of the rotation axis, with an amplitude of about 5 degrees and a period of about 22 days. The nutation parameters, as well as the precession of the apsis, with a period of about 274 years, are consistent with what is expected from the torques induced by the companion star.
Resumo:
Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.
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In this paper, we study binary differential equations a(x, y)dy (2) + 2b(x, y) dx dy + c(x, y)dx (2) = 0, where a, b, and c are real analytic functions. Following the geometric approach of Bruce and Tari in their work on multiplicity of implicit differential equations, we introduce a definition of the index for this class of equations that coincides with the classical Hopf`s definition for positive binary differential equations. Our results also apply to implicit differential equations F(x, y, p) = 0, where F is an analytic function, p = dy/dx, F (p) = 0, and F (pp) not equal aEuro parts per thousand 0 at the singular point. For these equations, we relate the index of the equation at the singular point with the index of the gradient of F and index of the 1-form omega = dy -aEuro parts per thousand pdx defined on the singular surface F = 0.
Resumo:
The use of liposomes to encapsulate materials has received widespread attention for drug delivery, transfection, diagnostic reagent, and as immunoadjuvants. Phospholipid polymers form a new class of biomaterials with many potential applications in medicine and research. Of interest are polymeric phospholipids containing a diacetylene moiety along their acyl chain since these kinds of lipids can be polymerized by Ultra-Violet (UV) irradiation to form chains of covalently linked lipids in the bilayer. In particular the diacetylenic phosphatidylcholine 1,2-bis(10,12-tricosadiynoyl)- sn-glycero-3-phosphocholine (DC8,9PC) can form intermolecular cross-linking through the diacetylenic group to produce a conjugated polymer within the hydrocarbon region of the bilayer. As knowledge of liposome structures is certainly fundamental for system design improvement for new and better applications, this work focuses on the structural properties of polymerized DC8,9PC:1,2-dimyristoyl-sn-glycero-3-phusphocholine (DMPC) liposomes. Liposomes containing mixtures of DC8,9PC and DMPC, at different molar ratios, and exposed to different polymerization cycles, were studied through the analysis of the electron spin resonance (ESR) spectra of a spin label incorporated into the bilayer, and the calorimetric data obtained from differential scanning calorimetry (DSC) studies. Upon irradiation, if all lipids had been polymerized, no gel-fluid transition would be expected. However, even samples that went through 20 cycles of UV irradiation presented a DSC band, showing that around 80% of the DC8,9PC molecules were not polymerized. Both DSC and ESR indicated that the two different lipids scarcely mix at low temperatures, however few molecules of DMPC are present in DC8,9PC rich domains and vice versa. UV irradiation was found to affect the gel fluid transition of both DMPC and DC8,9PC rich regions, indicating the presence of polymeric units of DC8,9PC in both areas, A model explaining lipids rearrangement is proposed for this partially polymerized system.
Resumo:
The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results.
Resumo:
We explicitly construct a stationary coupling attaining Ornstein`s (d) over bar -distance between ordered pairs of binary chains of infinite order. Our main tool is a representation of the transition probabilities of the coupled bivariate chain of infinite order as a countable mixture of Markov transition probabilities of increasing order. Under suitable conditions on the loss of memory of the chains, this representation implies that the coupled chain can be represented as a concatenation of i.i.d. sequences of bivariate finite random strings of symbols. The perfect simulation algorithm is based on the fact that we can identify the first regeneration point to the left of the origin almost surely.