Double-wave function of RLC circuit after quantization

Quantization of RLC circuit is given and described by a double-wave function. A comparison between classical limit result and those of classical theory is made.

Landauer-Buttiker formula for time-dependent transport through resonant-tunneling structures: A nonequilibrium Green's function approach

A nonequilibrium Green's-function formalism is employed to study the time-dependent transport through resonant-tunneling structures. With this formalism, we derive a time-dependent Landauer-Buttiker formula that guarantees current conservation and gauge invariance. Furthermore, we apply the formula to calculate the response behaviors of the resonant-tunneling structures in the presence of rectangular-pulse and harmonic-modulation fields. The results show that the displacement current plays the role of retarding the tunneling current.

Spectral properties of a double-quantum-dot structure: A causal Green's function approach

Spectral properties of a double quantum dot (QD) structure are studied by a causal Green's function (GF) approach. The double QD system is modeled by an Anderson-type Hamiltonian in which both the intra- and interdot Coulomb interactions are taken into account. The GF's are derived by an equation-of-motion method and the real-space renormalization-group technique. The numerical results show that the average occupation number of electrons in the QD exhibits staircase features and the local density of states depends appreciably on the electron occupation of the dot.

Cancer classification based on direction-basis-function neural networks

Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.

The structure and function of neurons with variable nonlinear transfer function

One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue of multi-thresholded, the variable transfer function neuron switch on among different nonlinear excitated state. And the comparison of output's transfer characteristics between it and single-thresholded neuron will be illustrated, with some practical application experiments on Bi-level logic operation, at last the simple comparison with conventional BP, RBF, and even DBF NN is taken to expect the development foreground on the variable neuron.. The novel nonlinear transfer function neuron could implement the random nonlinear mapping relationship between input layer and output layer, which could make variable transfer function neuron have one much wider applications on lots of reseach realm such as function approximation pattern recognition data compress and so on.

Simulation on Gain Recovery of Quantum Dot Semiconductor Optical Amplifiers by Rate Equation

The gain recoveries in quantum dot semiconductor optical amplifiers are numerically studied by rate equation models. Similar to the optical pump-probe experiment, the injection of double optical pulses is used to simulate the gain recovery of a weak continuous signal for the QD SOAs. The gain recoveries are fitted by a response function with multiple exponential terms. For the pulses duration of 10 ps, the gain recovery can be described by three exponential terms with the time constants, and for the pulse with the width of 150 fs, the gain recovery can be described by two exponential terms, the reason is that the short pulse does not consume lot of carriers.

On detection wavelength and electron-hole wave function overlap of type II InAs/In-x Ga1-x Sb superlattice infrared photodetector

In this paper, the detection wavelength and the electron-hole wave function overlap of InAs/IrxGa1-xSb type II superlattice photodetectors are numerically calculated by using the envelope function and the transfer matrix methods. The band offset is dealt with by employing the model solid theory, which already takes into account the lattice mismatch between InAs and InxGa1-xSb layers. Firstly, the detection wavelength and the wave function overlap are investigated in dependence on the InAs and InxGa1-xSb layer thicknesses, the In mole fraction, and the periodic number. The results indicate that the detection wavelength increases with increasing In mole fraction, InAs and InxGa1-xSb layer thicknesses, respectively. When increasing the periodic number, the detection wavelength first increases distinctly for small periodic numbers then increases very slightly for large period numbers. Secondly, the wave function overlap diminishes with increasing InAs and InxGa1-xSb layer thicknesses, while it enhances with increasing In mole fraction. The dependence of the wave function overlap on the periodic number shows the same trend as that of the detection wavelength on the periodic number. Moreover, for a constant detection wavelength, the wave function overlap becomes greater when the thickness ratio of the InAs over InxGa1-xSb is larger.

Formal specification and refinement of a safe train control function

Motivated by the design and development challenges of the BART case study, an approach for developing and analyzing a formal model for reactive systems is presented. The approach makes use of a domain specific language for specifying control algorithms able to satisfy competing properties such as safety and optimality. The domain language, called SPC, offers several key abstractions such as the state, the profile, and the constraint to facilitate problem specification. Using a high-level program transformation system such as HATS being developed at the University of Nebraska at Omaha, specifications in this modelling language can be transformed to ML code. The resulting executable specification can be further refined by applying generic transformations to the abstractions provided by the domain language. Problem dependent transformations utilizing the domain specific knowledge and properties may also be applied. The result is a significantly more efficient implementation which can be used for simulation and gaining deeper insight into design decisions and various control policies. The correctness of transformations can be established using a rewrite-rule based induction theorem prover Rewrite Rule Laboratory developed at the University of New Mexico.

function definition language fdl and its implementation

A Function Definition Language (FDL) is presented. Though designed for describing specifications, FDL is also a general-purpose functional programming language. It uses context-free language as data type, supports pattern matching definition of functions, offers several function definition forms, and is executable. It is shown that FDL has strong expressiveness, is easy to use and describes algorithms concisely and naturally. An interpreter of FDL is introduced. Experiments and discussion are included.

incomplete exponential sums over galois rings with applications to some binary sequences derived from z(2l)

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