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This paper is concerned with state filtering and the parameter estimation problem of noisy Hodgkin-Huxley neuronal model. The Cubature Kalman filter is applied to solve the joint estimation problem as an effective means of dealing with system noise and observation noise. The proposed state filtering method is based on the only measurable variable - membrane potential. In addition, the method is applicable...
For the first time, 10nm Si-based bulk FinFETs 6T SRAM (beta ratio = 2) with novel multiple fin heights technology is successfully demonstrated with 25% better static noise margin at 0.6 V than single fin-height baseline. Meanwhile, presented technology also provides advantage in SRAM cell size by 20% scaling down. It can furthermore offer potential of beyond 10nm Si-based CMOS computing circuit technology.
We consider the problem of estimation and classification of signals in presence of compositional noise, where the traditional techniques do not provide either a consistent estimator for signals or a robust distance for classification. We use a recently introduced comprehensive framework that: (1) uses a distance-based objective function for data alignment leading to a consistent estimator of signals,...
In ship angular deformation measurement, Kalman filter used to estimate the deformation angle requires accurate dynamic flexure parameters. Traditionally, these dynamic flexure parameters are empirically set according to previous experience or determined from previously collected experimental data. Inevitably, the Kalman filter will perform poorly when the current application environment is differ...
This study proposes a method to detect and mark the target object removed from the monitoring scene and the unknown object left in the monitoring scene. The present method uses the timeliness background to extract the foreground object and to mask the part that was unwanted. The foreground object was compared with the current frame, thus, the unreliable pixels were filtered out. By the identification...
This paper analyzes the performance of space-time decision feedback equalization (STDFE) assisted multiuser detection (MUD) for multiple-antenna space division multiple access (SDMA) systems to improve system capacity over dispersive fading channels. The MUD-STDFE receiver consists of a bank of matched filters and symbol-spaced feedforward filters (FFF) that both spatially and temporally whitens noise...
Electrocorticography (ECoG) is an emerging tool to map brain functions in the context of neurosurgical intervention. Previous mapping methods based on the event related power spectrum are prone to noise. To improve the robustness of cortical function mapping, general linear model (GLM), which has been widely used in the analysis of functional magnetic resonance imaging (fMRI) data, is applied to bandpass...
A novel nano-injection based imaging sensor is presented towards demanding applications in telecommunications, biophotonics, optical tomography, explosives detection and non-destructive material evaluation. The sensor can provide low noise levels concurrently with strong internal amplification, which results in a significant increase in the signal-to-noise levels compared to existing short-wave infrared...
Spectrum sensing is a key component of cognitive radio networks. Compared with the single user spectrum sensing, cooperative spectrum sensing can detect the existence of the primary signal for improving the inference accuracy. However, cooperation induces additional communications overhead. In this paper, we propose a new cooperative spectrum sensing scheme with a light communication overhead caused...
Traditional anomaly detection methods lack adaptive captivity in complex and heterogeneous network. Especially while facing high noise environments or the situation of updating profiles not in time, intrusion detection systems will have high false alarm rate. In this paper, a new anomaly detection algorithm based on hierarchical clustering, called ADBHC, is proposed. ADBHC generates clusters using...
This paper presents a new receiver framework for the cyclic-prefix free (CP-free) MIMO-OFDM system, equipped with the space-time block codes (ST-BC), over time varying multipath channels. Usually, without CP in the OFDM system the inter-carrier interference (ICI) could not be removed, effectively, at the receiver, when the inter-symbol-interference (ISI) has to be taken into account. In this paper,...
Most anomaly detection methods can not be fit for the changing and complex network. High noise and updating normality profiles not in time will lead to high false alarm rate. In this paper, a new anomaly detection algorithm using improved hierarchy clustering, called ADIHC, is proposed in this paper. It applies an improved hierarchy clustering tree to organize clusters which are obtained by density-based...
A 3.1-5 GHz Ultra Wideband (UWB) CMOS low noise amplifier (LNA) with high gain and noise cancellation is presented. The LNA is composed of two stages-an input common-gate stage with a resonant load at 3.1 GHz, driving a common source stage with a resonant load of 5 GHz. Noise cancellation is achieved through the forward feedback technique, and an output buffer has been added for test purposes. The...
Wavelet is commonly used at signal de-noise and the methodologies of wavelet de-noise become more and more scheming and complex. In this paper we propose a very simple but effective method, shifting-scale-method, to improve signal denoise using wavelet by firstly unveiling that low signal/noise coefficient ratio in wavelet domain is one of major baffles forwarding effective wavelet de-noising; then...
The candidate topologies for low-power, wideband LNAs are analyzed in this paper, and a novel LNA topology for the 3.1–5 GHz UWB frequency band is presented. The LNA uses subthreshold biasing and employs its Miller capacitance as part of a Butterworth-type bandpass filter for input impedance matching. The LNA achieves a power gain of 14.4 dB with S11 less than −10 dB across the 3.1–5 GHz frequency...
This paper presents a GPS positioning method based on neural network adaptive Kalman filter. Using the innovation vector which reflects the degree how the model fits the data, and real-timely accessing to the innovation vector's ratio of the theoretical variance to the actual of variance, we can get the working conditions of Kalman filter. Then track the change of system parameters through neural...
Model compensation is an important means to improve the robustness of speaker recognition in noise environment. The robust speaker recognition approach based on model compensation is proposed in this paper. The proposed method combines data reliability estimation and feature components effectiveness estimation, so the errors of the second kind due to the estimation error are reduced greatly. The proposed...
The evaluation of a product in terms of radiated emissions involves identifying the noise sources. Spectrum analyzer (SA) measurements alone are unable to identify noise sources when multiple sources are responsible for emissions at a particular frequency. In this paper, an approach using combined near-field and far-field measurements is proposed. This method consists of recording signals from a near...
In this paper, we propose an approach to segment the multiple objects in video. For a video sequence with stationary background, our approach combines the feature points with the color and contrast information to extract the multiple objects of different sizes. The idea is that the local features of the feature points are more robust than that of the pixels, and more accurate than the global color...
Resonant type capacitive MEMS transducers were fabricated using a multi-user MEMS process (MUMPs) for the detection of acoustic emission (AE). Electrical and mechanical characterization of the MEMS transducers has been performed. The performance of the transducers is limited by the noise. In this paper, we present the noise analysis, the discussion of noise sources, and show that Brownian noise plays...
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