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A novel time domain method based on improved multivariate empirical mode decomposition (MEMD) for plant-wide oscillations characterization is proposed. The original MEMD is ameliorated in the following aspects, (i) decorrelation of the two-dimensional Halton sequences, (ii) boundary processing to restrain end effect and (iii) improved criterion for sifting process stoppage. Due to its capability to...
Nowadays, Unmanned Aerial Vehicles(UAVs) have been widely applied in our life. However, the existing approach of interacting with UAVs, i.e., using a remote controller with control sticks, is not a natural and intuitive way. In this paper, we present a novel approach for users to interact with personal UAVs using wearable devices. The basic idea of our approach is to manipulate UAVs based on human...
Today's computing systems suffer from a memory/communication bottleneck, resulting in high energy consumption and saturated performance. This makes them inefficient in solving data-intensive applications at reasonable cost. Computation-In-Memory (CIM) architecture, based on the integration of storage and computation in the same physical location using non-volatile memristor crossbar technology, offers...
As today's CMOS technology is scaling down to its physical limits, it suffers from major challenges such as increased leakage power and reduced reliability. Novel technologies, such as memristors, nanotube, and graphene transistors, are under research as alternatives. Among these technologies, memristor is a promising candidate due to its great scalability, high integration density and near-zero standby...
We propose to use a feature representation obtained by pairwise learning in a low-resource language for query-by-example spoken term detection (QbE-STD). We assume that word pairs identified by humans are available in the low-resource target language. The word pairs are parameterized by a multi-lingual bottleneck feature (BNF) extractor that is trained using transcribed data in high-resource languages...
CMOS technology and its sustainable scaling have been the enablers for the design and manufacturing of computer architectures that have been fuelling a wider range of applications. Today, however, both the technology and the computer architectures are suffering from serious challenges/ walls making them incapable to deliver the right computing power at pre-defined constraints. This motivates the need...
Many emerging technologies are under investigation to realize alternatives for future scalable electronics. Memristor is one of the most promising candidates due to memrsitor's non-volatility, high integration density, near-zero standby power consumption, etc. Memristors have been recently utilized in non-volatile memory, neuromorphic system, resistive computing architecture, and FPGA to name but...
Using speech or text to predict articulatory movements can have potential benefits for speech related applications. Many approaches have been proposed to solve the acoustic-to-articulatory inversion problem, which is much more than the exploration for predicting articulatory movements from text. In this paper, we investigate the feasibility of using deep neural network (DNN) for articulartory movement...
Recently, deep and/or recurrent neural networks (DNNs/RNNs) have been employed for voice conversion, and have significantly improved the performance of converted speech. However, DNNs/RNNs generally require a large amount of parallel training data (e.g., hundreds of utterances) from source and target speakers. It is expensive to collect such a large amount of data, and impossible in some applications,...
Adaptability and controllability are the major advantages of statistical parametric speech synthesis (SPSS) over unit-selection synthesis. Recently, deep neural networks (DNNs) have significantly improved the performance of SPSS. However, current studies are mainly focusing on the training of speaker-dependent DNNs, which generally requires a significant amount of data from a single speaker. In this...
Crosstalk cancellation is an important issue in loudspeaker-based virtual auditory. Most of the correlated researches focus on far-field situation. This paper addresses near-field crosstalk cancellation problem, which has more challenges and seldom been addressed. Firstly loudspeaker can no longer be modeled as point source so that the head related transfer functions (HRTF) is very difficult to measure...
In this paper, a novel structure named as quasidouble silicon-on-insulator metal-oxide-semiconductor transistor (SOI MOSFET) is proposed. Compared with the structure of normal SOI MOSFET, ultrathin oxide layers and p+ wells are added under the source and drain regions, which successfully isolate the source and drain from the buried oxide (BOX). The ultrathin oxide layers prevent the leakage current...
From the varying threshold voltage of MOSFET caused by the external factor, this paper analyzes the variation tendency of amplifier's gain. It makes clear how the gain of three different amplifiers changes in theoretical. After that, EDA tools are utilized to verify the theoretical calculation. The theoretical and simulation result show that threshold voltage(Vth) is a sensitive parameter of amplifier's...
This paper investigates the reliability of junctionless MOSFETs based inverter by 3D TCAD simulation. The results show the I–V behavior of junctionless SOI-MOSFETs is highly resistant to accumulated fixed charge in oxide. Then the performance of junctionless device-based inverter is discussed. VM of juncitonless device-based inverter maintains within 0.05V and the transient response time shows very...
As a basic logic unit of integrated circuit, the stability of parameters of inverter have a direct effect on the performance of system. This paper starts from parametric drift of traditional inverter caused by the variation of threshold voltage of MOSFET. Then a new parametric drift-resistant inverter is proposed. This structure utilizes compensation circuit to solve parametric drift such as the decrease...
In this paper, the primary user emulation attack (PUEA) detection problem in the cognitive radio network (CRN) with mobile secondary user (SU) is investigated. We propose a hybrid PUEA detection method, in which two kinds of wireless channel characteristics between the transmitter and the receiver, the Doppler spread and the variance of the received signal power, are utilized to infer the source of...
We present a neural network based punctuation prediction method using Long Short-Term Memory (LSTM) network. The proposed method uses bidirectional LSTM to encode both the past and future observation as its inputs. It models the dependency between input features and output labels through multiple layers. We also empirically study the impacts of modeling the dependency between output labels. Our results...
Polyphone disambiguation in Mandarin Chinese aims to pick up the correct pronunciation from several candidates for a polyphonic character. It serves as an essential component in human language technologies such as text-to-speech synthesis. Since the pronunciation for most polyphonic characters can be easily decided from their contexts in the text, in this paper, we address the polyphone disambiguation...
We use query-by-example keyword spotting (QbyE-KWS) approach to solve the personalized wake-up word detection problem for small-footprint, low-computational cost on-device applications. QbyE-KWS takes keywords as templates, and matches the templates across an audio stream via DTW to see if the keyword is included. In this paper, we use neural networks as acoustic models to extract DNN/LSTM phoneme...
Currently, conventional indoor localization schemes mainly leverage WiFi-based or Bluetooth-based schemes to locate the users in the indoor environment. These schemes require to deploy the infrastructures such as the WiFi APs and Bluetooth beacons in advance to assist indoor localization. This property hinders the indoor localization schemes in that they are not scalable to any other situations without...
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