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This paper presents the implementation of an adaptive fading multiplicative extended Kalman filter (AFMEKF), applied to the problem of attitude estimation in the context of quadrotors. The extended Kalman filter is adapted for use with quaternions and made adaptive to account for inaccurate measurement information. Simulations have been conducted in order to validate the filter performance.
This paper provides a novel formulation relating underwater range measurements to body-fixed position when several acoustic transceivers are mounted on the vehicle and only one transponder is placed in the vehicle's surroundings. This formulation is used in a novel three-stage filter for aided inertial navigation that has both global convergence and near-optimal performance w.r.t. variance of the...
We consider distributed filtering of a scalar linear stochastic process under communication corrupted by Gaussian noise. We investigate how communication noise degrades the performance of an existing distributed algorithm and develop a novel algorithm that mitigates these problems. We rigorously investigate the properties of the new distributed estimator and discuss optimal tuning of (fixed) gains...
In this paper we propose a novel mission control strategy for a group of agents to locate an unknown source, represented as maximum of a scalar field, and to track a specified level curve. We propose a distributed control scheme based on hierarchy formation and reduced topology. Without prior knowledge of the field, the agents, equipped with local sensors, navigate in ℝp using an estimated gradient...
We develop an algorithm that can detect the identity of false data-injection attackers in distributed optimization loops for estimating oscillation modes in power system models when the measurements used for the estimation are noisy. The fundamental set-up for the optimization is based on a distributed version of total least-squares (TLS) executed via Alternating Direction Multiplier Method (ADMM)...
In this study, an automatic trace-based approach is presented for reducing Gaussian noise in color images. As a first step in the method, homogeneous regions in the noisy image are detected. As a second step, the variance of additive white Gaussian noise is estimated by taking into account the detected homogeneous regions. As a final step, the noise reduction process is performed via an improved trace-based...
With the assumption that natural images contain considerable amount of self-similarity, non-local means image de-noising uses patches similarity in order to filter noisy images. Although the output of the Non local means algorithm is very desirable in removing the low level of noise, when the noise increases, the performance deteriorates. This is because the similarity cannot be evaluated perfectly...
The problem of joint parameters and time delay estimation or their tracking by processing of input-output observations arises, when LTI dynamical system has an unknown time delay. It is known that a mean-square error function is multiextremal for time delay even if the system parameters are known in advance. For this purpose an approach used to transform the multiextremal criterion into an unimodal...
On a power network, events are desired to be monitored to find its reasons and to take preventive action. Today, power quality measurement devices are used to obtain synchronous measurement data of network, however these devices are expensive and it is not considered a practical option to place one on each node of the network. Therefore, methods estimating voltages and currents at non-measured points...
In hands-free mobile communication, speech quality is often degraded due to presence of surrounding noise. This paper introduces an improved version of Minimum Mean Square Error (MMSE) noise estimator. Noise spectrum estimation is a crucial element used in speech recognition systems. Our proposed noise estimation method is based on a popular searching algorithm used in software engineering called...
Microtubules play an essential role in many cellular processes whose disrupted functioning is associated with devastating human diseases such as cancer. The discovery and testing of microtubule targeting drugs often involve time-lapse fluorescence microscopy imaging of microtubule plus-end binding proteins and require highly accurate estimation of their dynamic behavior. Although many methods exist...
Recently unmanned aerial vehicles have become one of the most interesting research topics among scientists. Although researchers are very concerned in this area, they generally use the same dynamical plant equations. Simulations using that ready-to-use plant equations are common methods in order to apply control or optimization theories. But, beyond simulations, in real time control of these systems...
Direct Sequence Spread Spectrum (DSSS) signal has been widely used because of its low signal-to-noise ratio, strong anti-interference, low interception rate and multi-path effect. It is gradually replacing the traditional communications, and widely used in modern military and commercial communications systems. Therefore, the corresponding direct-communication communication reconnaissance technology...
The demonstration presents a real-time mockup of smartphone- based hearing aid with combined noise and acoustic feedback reduction. The designed reduction algorithm is based on spectral weighting approach which makes it very robust to rapid changes in feedback path either caused by displacement of the speaker/microphone or room acoustics. The aim of the demonstration is to show potential of the implemented...
We demonstrate the feasibility of the realtime implementa- tion of advanced binaural noise reduction algorithms in a single-chip computer called Raspberry Pi. The implementa- tion of the considered algorithms is realized in Simulink, a graphical programming add-on to the integrated development environment Matlab. Using a complementary support pack- age for Simulink, the Raspberry Pi is connected/hosted...
Most of multichannel sound source Direction Of Arrival (DOA) estimation algorithms suffer from spatial aliasing problems. The phase differences between a pair of microphones are wrapped beyond the spatial aliasing frequency. A common solution is to adjust the distance between the microphones to obtain a suitable aliasing frequency, and take only the frequency band below the aliasing frequency for...
Pitch is an important characteristic of speech and is useful for many applications. However, it is still challenging to estimate pitch in strong noise. In this paper, we propose a joint training approach to determinate pitch. First, a Bidirectional Long Short-Term Memory Recurrent Neural Networks (BLSTMRNN) is trained to map the noisy to clean speech features. Second, the pitch estimation is also...
Reverberation and noise are known to be the two most important culprits for poor performance in far-field speech applications, such as automatic speech recognition. Recent research has suggested that reverberation-aware speech enhancement (or speech technologies, in general) could be used to improve performance. However, recent results also show existing blind room acoustics characterization algorithms...
We consider the problem of estimating the covariance matrix and the transition matrix of vector autoregressive (VAR) processes from partial measurements. This model encompasses settings where there are limitations in the data acquisition of the underlying measurement systems so that data is lost or corrupted by noise. An estimator for the covariance matrix of the observations is first presented. More...
Here we propose online adaptive beamforming for automatic speech recognition (ASR) in meetings in noisy, reverberant environments. The proposed method is based on recently developed mask-based beamforming, in which accurate mask estimation and diarization are paramount. Real-world experiments have shown that mask-based beamforming enables accurate ASR in meetings in small noise and reverberation with...
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