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An analytical surface-potential-based drain current model for amorphous indium–gallium–zinc–oxide (a-InGaZnO) thin film transistors (TFTs) is proposed by introducing an effective charge density approach in this paper. This approach gives two initial approximate values of the effective state density and the effective thermal voltage by using the dominant state of the free charge density in total charge density, and then obtains a high-precision one-exponent equivalent transformation for three-exponent total charge density. Based on this approach, we have solved the problem that the physical meaning of the transition area in the regional method is not clear and a one-piece analytical surface potential solution to Poisson's equation is successfully derived. Furthermore, the drain current is also explicitly derived from the charge sheet model and I-V characteristics of a-InGaZnO TFTs are reproduced from the above obtained model. Finally, accurate and effective surface-potential model and drain current model are obtained and verified by experimental data, respectively. Good verification results prove that the proposed model could become an accurate and suitable tool for being embedded into a circuit simulation. [ABSTRACT FROM AUTHOR]

As a key to simulate electrostatic characteristics of solar cells and implement single-diode model into simulators, a noniterative parameter-extraction method is proposed to determine five parameters of single-diode model. It is straightforwardly derived from the transcend equation set of terminal ${I} - {V}$ equations to overcome the imperfections of poor efficiency in numerical iteration methods, low accuracy in semiempirical approaches, and absence of physical meaning in optimization algorithms. As a result, such a parameter-extraction method actually serves as a useful tool to acquire model parameters, analyze preparing process’ results, and expand practicability of lumped parameter model. [ABSTRACT FROM AUTHOR]

Three-diode lumped-parameter equivalent circuit model conforms to photovoltaic device physics and processes an exact analysis for I – V characteristics of industrial solar cells, because it explains the different leakage current components especially for recombination current resulting from defects or grain boundaries. However, three-diode model’s complete circuit topology leads to complicated transcendental I – V equation without analytical solution so that low computation efficiency limits three-diode model’s applications in photoelectric simulations. In this article, an effective-diode method is proposed to simplify three-diode model, derive accurate and efficient terminal current–voltage solution to three-diode model, and acquire electrostatic characteristics of the solar cells. The calculated values have good agreements with numerical iteration results and experimental data measured from solar cells, respectively. Finally, the effective-diode method performs an important role of solving three-diode model analytically, predicting I – V characteristics of industrial solar cells accurately, and providing three-diode model’s practicability and development in solar cells’ simulations. [ABSTRACT FROM AUTHOR]

A lumped-parameter circuit model is proposed to describe the S-shaped I-V characteristics with current kinks exhibited in perovskite solar cells (PSCs). The physics-based model represents the electrical effect of the electrode contact interface. A Difference-Microvariation (DM) principle is used to derive the explicit solution of the model, which gives accurate and efficient descriptions for the current kinks of PSCs in a single-piece formula. The good agreement between our proposed model and numerical iteration results or reconstructed experimental data proves its validity. We believe that, the improved model can provide optimization direction for device process. Meanwhile, the proposed DM principle can perform as an efficient and serviceable tool to implement the lumped-parameter model compactly into TCAD simulators of PSCs. [ABSTRACT FROM AUTHOR]

A parameter extraction routine for three-diode lumped parameter model of organic solar cells (OSCs) based on particle swarm optimization (PSO) is presented in this letter. In the process of parameter extraction by using PSO, we overcome the problem of encountering locally optimal solutions, where such a problem results from the similar effects of some parameters on ${I} - {V}$ characteristics. Combining with the analytical solution algorithm of OSCs’ three-diode lumped parameter model, our parameter extraction routine can efficiently acquire the accurate fitting parameters to complete simulations for ${I} - {V}$ characteristics. Furthermore, this routine is valid for the different algorithms of the solution to OSCs’ ${I} - {V}$ properties. Finally, we use the experimental data measured from OSCs to verify the parameter extraction routine. As a result, such a parameter extraction routine can perform as an important tool to extract the fitting parameters of OSCs’ lumped parameter model. [ABSTRACT FROM AUTHOR]

A lumped-parameter equivalent circuit model is proposed to simulate the S-shaped current–voltage (${I}$ – ${V}$) characteristics exhibited in organic solar cells. First, we derive an explicit terminal current solution as a function of terminal voltage from the equation set of the three-diode lumped-parameter model proposed by Mazhari. Second, we improved Mazhari’s model to improve the accuracy and developed the explicit solution of our improved model to improve the efficiency. Third, we use the method of least squares, Newton–Raphson root-finding scheme, and experimental data to validate the solutions of Mazhari’s and our models. As a result, owing to high accuracy and efficiency of computation, our explicit calculation scheme, regarded as a useful tool, can help to implement Mazhari’s and our models into photovoltaic device and system simulators in compact format. [ABSTRACT FROM AUTHOR]

An analytical surface-potential-based drain current model of dynamic-depletion (DD) polysilicon (poly-Si) thin-film transistors (TFTs) is proposed in this paper. In the 1-D Poisson equation, total charge density is reformulated by an effective charge density, which allows a closed-form surface potential calculation scheme. Different boundary conditions between partial depletion and full depletion are calculated and unified into one back-gate potential in the DD mode, which allows a unified-form surface potential calculation scheme. Combining with Gauss’s theory, we explicitly solve a closed- and unified-form surface potential of DD poly-Si TFTs. Based on the solution of the surface potential, the drain current is derived analytically from the Pao–Sah integration. Furthermore, our solution is verified by numerical results and experimental data, respectively. As a result, such a model can accurately predict I–V characteristics of DD poly-Si TFTs and provide computational efficiency for TFT process optimization and circuit simulations. [ABSTRACT FROM AUTHOR]

We propose an explicit surface-potential-based direct current (dc) model for fully depleted polysilicon (poly-Si) thin-film transistors (TFTs). Being analytical and explicit, the proposed model is a solid base for compact models of these devices. The essential for our model is the explicit calculation of the surface potential, using the Lambert W function. Subsequently, using the surface potential, we also develop the expressions for charge and current, employing well established approaches, which include integration of carrier’s charge for drain current. Furthermore, the solutions of surface potential and drain current were validated by numerical results and experimental data, respectively. Finally, we discussed in detail about the effects on the surface potential and dc properties from the full depleted poly-Si TFT parameters. As a result, such a model is suitable to be implemented into computer-aided simulations of both device and circuit designs, due to its high computational accuracy and efficiency. [ABSTRACT FROM AUTHOR]

An analytical surface-potential-based drain current model of symmetric double-gate (sDG) MOSFETs is described as a SPICE compatible model in this paper. The continuous surface and central potentials from the accumulation to the strong inversion regions are solved from the 1-D Poisson’s equation in sDG MOSFETs. Furthermore, the drain current is derived from the charge sheet model as a function of the surface potential. Over a wide range of terminal voltages, doping concentrations, and device geometries, the surface potential calculation scheme and drain current model are verified by solving the 1-D Poisson’s equation based on the least square method and using the Silvaco Atlas simulation results and experimental data, respectively. Such a model can be adopted as a useful platform to develop the circuit simulator and provide the clear understanding of sDG MOSFET device physics. [ABSTRACT FROM AUTHOR]

Classification of video sequences is an important task with many applications in video search and action recognition. As opposed to some traditional approaches that transform original video sequences into forms of visual feature vectors, tensor-based methods have been proposed for classifying video sequences with natural representation of original data. However, one obvious limitation of tensor-based methods is that the input video sequences are often required to be preprocessed with a unified length of time. In this paper, we propose a technique for handling classification of video sequences in unequal length of time, namely Spatial-Temporal Iterative Tensor Decomposition (S-TITD) for uniform length. The proposed framework contains two primary steps. We first represent original video sequences as a third-order tensor and perform Tucker-2 decomposition to obtain the reduced-dimension core tensor. Then we encode the third order of core tensor to a uniform length by adaptively selecting the most informative slices. Notably, the above two steps are embedded into a dynamic learning framework to guarantee the proposed method has the ability of updating results over time. We conduct a series of experiments on three public datasets in gesture and action recognition, and the experimental results show that the proposed S-TITD approach achieves better performances than the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

The task of video sequence classification plays a critical role in the development of computer vision. Considering this fact, this letter proposes a novel tensor decomposition method called tensor-driven temporal correlation in which general tensors are used as input for video sequence classification. Because distortion and redundancy may exist in the tensor representations of video sequences, we project the original tensor into subspaces spanned by spatial basis matrices in the proposed formulation. Moreover, to better preserve the temporal smoothness between consecutive slices of the tensor, the basis matrices are jointly learned by introducing an autoregressive model. An experiment on the commonly used Cambridge hand-gesture database demonstrates that our proposed method reaches convergence within a small number of iterations during the training stage and achieves promising results compared with state-of-the-art methods. [ABSTRACT FROM PUBLISHER]

A non-iterative method is presented to accurately extract the five parameters of single diode model of solar cells in this paper. This method overcomes the problems of complexity and accuracy by simplifying the calculation process. Key parts of the equation are to be adjusted dynamically so that the desired five parameters can be obtained from the I-V curve. Then, the I-V and P-V characteristic curves of solar cells are used to compare the effectiveness of this method with other methods. Furthermore, the root mean square error analysis shows that this method is more applicable than other methods. Finally, the I-V and P-V characteristics simulated by using the extracted parameters in this method are compared and discussed with the experimental data of solar cells under different conditions. In fact, this extraction process can be regarded as an effective and accurate method to estimate solar cells' single diode model parameters. [ABSTRACT FROM AUTHOR]

A surface-potential-based analytical I-V model of single-gate (SG) silicon-on-insulator (SOI) MOSFETs in full-depletion (FD) mode is proposed and compared with numerical data and Khandelwal's experimental results. An explicit calculation scheme of surface potential, processing high computation accuracy and efficiency, is demonstrated according to the derivation of the coupling relation between surface potential and back-channel potential. The maximum absolute error decreases into 10−7 V scale, and computation efficiency is improved substantially compared with numerical iteration. Depending on the surface potential, the drain current is derived in closed-form and validated by Khandelwal's experimental data. High computation accuracy and efficiency suggest that this analytical I-V model displays great promise for SOI device optimizations and circuit simulations. [ABSTRACT FROM AUTHOR]

We propose an improved lumped-parameter equivalent circuit model to describe S-shaped I–V kinks observed from organic solar cells. Firstly, to predict the S-shaped I–V kinks accurately in both the first and fourth quadrants, a shunt resistor in parallel with extraction diode is added to our previous model. Secondly, based on the Newton–Raphson method, we derive a solution to our improved circuit. Thirdly, our solution is verified by the method of least squares and experiments. Finally, compared with our previous work, the improved circuit has higher accuracy in demonstrating S-shaped I–V kinks in the first and fourth quadrants. Such an improved model is suitable for circuit simulations of organic solar cells. [ABSTRACT FROM AUTHOR]

An improved lumped-parameter equivalent circuit model is proposed to describe S-shaped I–V characteristics of organic solar cells (OSCs). This model originates but differs from Mazhari’s model. As a minor but important modification, a shunt resistance is added to Mazhari’s model to increase the accuracy of simulating the S-shaped kink in the third quadrant. Subsequently, we present a terminal current-voltage equation set and derive an analytical solution to the improved model. Furthermore, we verify the analytical solution to our model by using the least square method and validate our model by using the experimental I–V curves examined from OSCs. Compared with Mazhari’s model, our model has greater accuracy in interpreting the S-shaped kink with linear-like rise in the third quadrant. As a result, our improved model is suitable to explain the S-shaped I–V characteristics of organic solar cells in the whole operational region, especially for the S-shaped kink in the third quadrant. [ABSTRACT FROM AUTHOR]

In this paper, an analytical and closed-form solution to the lumped parameter equivalent circuit model of organic solar cells is proposed to complete the simulations of the S-shaped I-V characteristics. Based on the model previously proposed by Mazhari, the set of terminal current and voltage equations describing the three diodes is solved and the effects from the model parameters are illustrated. Our solutions are verified by being compared with the least square method results and experimental data, respectively. Good agreements show that our solution calculation scheme is not only both accurate and efficient, but also valid in the whole operation regime of solar cells, especially for the S-shaped kink on the condition where the terminal voltage is larger than the open circuit voltage. Such an analytical solution can play an important role in the simulations for I-V characteristics of solar cells, fast extractions of the model parameters, and implements into practical photovoltaic device simulators. [ABSTRACT FROM AUTHOR]

Recently, considerable efforts have been made in visual search reranking towards refining initial text-based image search results. In this paper, we propose a hypergraph based semi-supervised ranking method called HyperSSR for image search reranking. According to the basic visual consistency principle that visually similar images should have similar ranking scores, we introduce the hypergraph to capture the intrinsic geometrical structure of the data distribution. To build a robust hypergraph, a novel hypergraph construction approach is developed to incorporate relevance and pseudo relevance degree information from labeled and unlabeled samples, respectively. Based on the premise that a ranking model should work better with the prior pairwise preferences, we jointly incorporate the hypergraph regularizer and the prior pairwise preferences information into a unified ranking learning framework. Experimental results on MSRA-MM 1.0 dataset suggest our proposed approach produces superior performances compared with several state-of-the-art methods. [ABSTRACT FROM AUTHOR]