4 resultados para Code-switching

em CaltechTHESIS


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A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

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The complex domain structure in ferroelectrics gives rise to electromechanical coupling, and its evolution (via domain switching) results in a time-dependent (i.e. viscoelastic) response. Although ferroelectrics are used in many technological applications, most do not attempt to exploit the viscoelastic response of ferroelectrics, mainly due to a lack of understanding and accurate models for their description and prediction. Thus, the aim of this thesis research is to gain better understanding of the influence of domain evolution in ferroelectrics on their dynamic mechanical response. There have been few studies on the viscoelastic properties of ferroelectrics, mainly due to a lack of experimental methods. Therefore, an apparatus and method called Broadband Electromechanical Spectroscopy (BES) was designed and built. BES allows for the simultaneous application of dynamic mechanical and electrical loading in a vacuum environment. Using BES, the dynamic stiffness and loss tangent in bending and torsion of a particular ferroelectric, viz. lead zirconate titanate (PZT), was characterized for different combinations of electrical and mechanical loading frequencies throughout the entire electric displacement hysteresis. Experimental results showed significant increases in loss tangent (by nearly an order of magnitude) and compliance during domain switching, which shows promise as a new approach to structural damping. A continuum model of the viscoelasticity of ferroelectrics was developed, which incorporates microstructural evolution via internal variables and associated kinetic relations. For the first time, through a new linearization process, the incremental dynamic stiffness and loss tangent of materials were computed throughout the entire electric displacement hysteresis for different combinations of mechanical and electrical loading frequencies. The model accurately captured experimental results. Using the understanding gained from the characterization and modeling of PZT, two applications of domain switching kinetics were explored by using Micro Fiber Composites (MFCs). Proofs of concept of set-and-hold actuation and structural damping using MFCs were demonstrated.

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Proper encoding of transmitted information can improve the performance of a communication system. To recover the information at the receiver it is necessary to decode the received signal. For many codes the complexity and slowness of the decoder is so severe that the code is not feasible for practical use. This thesis considers the decoding problem for one such class of codes, the comma-free codes related to the first-order Reed-Muller codes.

A factorization of the code matrix is found which leads to a simple, fast, minimum memory, decoder. The decoder is modular and only n modules are needed to decode a code of length 2n. The relevant factorization is extended to any code defined by a sequence of Kronecker products.

The problem of monitoring the correct synchronization position is also considered. A general answer seems to depend upon more detailed knowledge of the structure of comma-free codes. However, a technique is presented which gives useful results in many specific cases.

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Part I. Complexes of Biological Bases and Oligonucleotides with RNA

The physical nature of complexes of several biological bases and oligonucleotides with single-stranded ribonucleic acids have been studied by high resolution proton magnetic resonance spectroscopy. The importance of various forces in the stabilization of these complexes is also discussed.

Previous work has shown that purine forms an intercalated complex with single-stranded nucleic acids. This complex formation led to severe and stereospecific broadening of the purine resonances. From the field dependence of the linewidths, T1 measurements of the purine protons and nuclear Overhauser enhancement experiments, the mechanism for the line broadening was ascertained to be dipole-dipole interactions between the purine protons and the ribose protons of the nucleic acid.

The interactions of ethidium bromide (EB) with several RNA residues have been studied. EB forms vertically stacked aggregates with itself as well as with uridine, 3'-uridine monophosphate and 5'-uridine monophosphate and forms an intercalated complex with uridylyl (3' → 5') uridine and polyuridylic acid (poly U). The geometry of EB in the intercalated complex has also been determined.

The effect of chain length of oligo-A-nucleotides on their mode of interaction with poly U in D20 at neutral pD have also been studied. Below room temperatures, ApA and ApApA form a rigid triple-stranded complex involving a stoichiometry of one adenine to two uracil bases, presumably via specific adenine-uracil base pairing and cooperative base stacking of the adenine bases. While no evidence was obtained for the interaction of ApA with poly U above room temperature, ApApA exhibited complex formation of a 1:1 nature with poly U by forming Watson-Crick base pairs. The thermodynamics of these systems are discussed.

Part II. Template Recognition and the Degeneracy of the Genetic Code

The interaction of ApApG and poly U was studied as a model system for the codon-anticodon interaction of tRNA and mRNA in vivo. ApApG was shown to interact with poly U below ~20°C. The interaction was of a 1:1 nature which exhibited the Hoogsteen bonding scheme. The three bases of ApApG are in an anti conformation and the guanosine base appears to be in the lactim tautomeric form in the complex.

Due to the inadequacies of previous models for the degeneracy of the genetic code in explaining the observed interactions of ApApG with poly U, the "tautomeric doublet" model is proposed as a possible explanation of the degenerate interactions of tRNA with mRNA during protein synthesis in vivo.