AASRI Procedia最新文献

The high voltage (HV) lateral double-diffused MOS (LDMOS) has a much lower on-resistance, a higher tolerance to breakdown voltage and a higher output power used for automotive ICs and high-frequency communication modules. However, its shortcomings are evident, including a high trigger voltage (V_t1), low holding voltage (V_h), low ESD discharge capability per unit length and multi-fingers unable to fully turn-on, which are serious impacted the ESD reliability capability. In this paper, the HV-nLDMOS device with adding field-oxide-devices (FODs) in the bulk area to make the trigger voltage effectively decreased, and in order to increase the ESD capability is investigated. Furthermore, the influence of bulk P⁺ area which was replaced by FODs in the bulk region on snapback parameters in a 0.25-μm 60-V high voltage process is evaluated. After that, the ESD capability has grate increased while the device with adding any FOD structures in the 0.25-μm 60-V high voltage process. The I_t2 value is > 7A and to be increased > 111.74% than that of a reference group. Noteworthy, this structure may make the trigger voltage (V_t1) too low to operate normally. Therefore, it should be careful considered that the problem of maximum FOD occupied ratio while using this methodology.

Spectrum sensing is used in cognitive radio systems to detect the availability of spectrum holes for secondary usage. The simplest and most famous spectrum sensing techniques are based either on energy detection or eigenspace analysis from Random Matrix Theory (RMT) such as using the Marchenko-Pastur law. These schemes suffer from uncertainty in estimating the noise variance which reduces their performance. In this paper we propose a new method to evaluate the noise variance that can eliminate the limitations of the aforementioned schemes. This method estimates the noise variance from a measurement set of noisy signals or noise-only signals. Extensive simulations show that the proposed method performs well in estimating the noise variance. Its performance greatly improves with increasing numbers of measurements and also with increasing numbers of samples taken per measurement.

This article introduced an accurate to ascertain the size of fine grinding medium. Comparative grinding tests are done by using cast iron segment steel ball. Grinding test results showed that mill capacity and grinding efficiency of cast iron segment could be really superior to steel ball. Grinding and flotation indexes have gotten obvious improvement when applying optimized fine grinding medium for industrial experiment.

Initial weight choice is an important aspect of the training mechanism for sigmoidal feedforward artificial neural networks. Usually weights are initialized to small random values in the same interval. A proposal is made in the paper to initialize weights such that the input layer to the hidden layer weights are initialized to random values in a manner that weights for distinct hidden nodes belong to distinct intervals. The training algorithm used in the paper is the Resilient Backpropagation algorithm. The efficiency and efficacy of the proposed weight initialization method is demonstrated on 6 function approximation tasks. The obtained results indicate that when the networks are initialized by the proposed method, the networks can reach deeper minimum of the error functional during training, generalize better (have lesser error on data that is not used for training) and are faster in convergence as compared to the usual random weight initialization method.

In this study, the acoustic echo problem and cancellation method of Android-platform-based VoIP was analyzed and researched. The echo problem is consequential for Android phone-based VoIP applications. However, in the traditional 2G/3G circuit-switch (CS) mode, the acoustic echo is cancelled by the hardware chip, and the quality of communication is adequate. In the future 4G/LTE environment, all-IP packet communication will be achieved. The IMS/VoIP will become the main application for personal speech communication systems. Before the introduction of 4G with echo cancellation built into its chip, the Android-based VoIP on 3.5G/WiFi will continue to undergo the aforementioned acoustic echo problem. This paper presents an analysis of the acoustic echo on Android-based VoIP and proposes a simple echo cancellation method.

Due to advancements in technology, many integrated circuits are fabricated to develop an artificial system that could perform “intelligent” tasks similar to those performed by the human brain. Many of them use off-chip learning method either by analog hardware or massively by parallel computers. This proposed work is about a trainable neural chip using Field Programmable Gate Array (FPGA) as this helps in learning capability by exploiting the inherent parallelism of neural network. By this fast prototyping is possible for real-time applications, such as speech recognition, speech synthesis, image processing, pattern recognition and classification. In this work on-chip learning method is designed for standard benchmark XOR problem using back propagation based multilayer perceptron and is implemented in VIRTEX-E FPGA using VHDL. The design works at 5.332 MHz and the total gate count is 4, 73,237.

This paper presents a proposal of digital mediation for enhancing the communication between sports media and its user community. The proposal is based on a conceptual model and a proof of concept in the form of a Web application. It is believed that the proposed application can contribute to enrich sports media Web portals with innovative features and to strengthen the relationship with their user community, exploiting the potential contributions of its members. This project also aims at fostering user participation and sharing of opinions in sports media Web portals.

A-SMAC protocol based on sensor node data traffic dynamic adjusting node listen and sleep time. Based on A-SMAC protocol, sensor nodes sent out the underlying error decisions .In this paper, we propose an adaptive fault-tolerant algorithm (AFTA) of node. According to the results of fault tolerant judgment, use of A-SMAC protocol dynamic adjusting node listen and sleep time, realize the combination of data judgment and node dynamic listening. Our experimental results show that the AFTA outperforms the Bayesian algorithm and exhibits strong fault-tolerant capabilities and less energy consume.

In the paper we suggested a method for video sequence handling with the aim of producing a single noise- free image. An algorithm for the image alignment based on the approaches of dot matches search and the resolution capacity enhancement has been elaborated. A method for multiple images stacking has been proposed to produce a single noise-free picture. The proposed method has been successfully experimentally tested using developed software tools.

In this paper a new technique is introduced for bias compensation of gyroscopes with a focus on mobiles phones. The standard problem of using gyroscopes is that integration of raw angular rates with non-zero bias will lead to continuous drift of the estimated orientation. To examine the nature of this bias, a simple error model was constructed for the whole device in terms of inertial sensing. For eliminating the bias, a sensor fusion algorithm was developed using the benefits of optical flow from the camera of the device. Our orientation estimator and bias removal method is based on complementary filters, in combination with an adaptive reliability filter for the optical flow features. The feedback of the fused result is combined with the raw gyroscope angular rates to compensate the bias. Various measurements were recorded on a real device running the demanding optical flow onboard. This way a robust and reliable fusion was constructed, which matched our expectations, and has been validated with simulations and real world measurements.