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The design of assistive technologies such as non-invasive brain computer interfaces (BCI) requires an improved understanding of the cortical dynamics of the human brain when interacting with new tools and/or adapting to novel environments in ecological situations. Therefore the aim of this study was to investigate potential biomarkers able to reflect dynamic cognitive-motor states of subjects who...
A novel image feature extraction methodology is proposed in this study. By incorporating fuzzy logic into the well-established Local Binary Pattern (LBP) approach we derive statistical feature distributions suitable for noise-robust texture representation. The proposed Fuzzy Local Binary Pattern (FLBP) approach is based on the assumption that a local image neighbourhood may be characterized by more...
Amplitude modulated sinusoidal signals arise in a wide variety of applications, e.g. in nuclear magnetic resonance spectroscopy [1], Doppler radar [2], and wide-band frequency-modulated continuous-wave radar signal processing. In some cases the type of amplitude modulation, e.g. exponential or polynomial, is known a priori, whereas in most practical cases such detailed information is not available...
The aim of the present research is to explore the application of sparse coding principles to the processing within a cochlear implant. These principles would determine what information in noisy speech should be extracted and used to excite the electrode array within the cochlea. The hypothesis is that reducing redundancy in the signal, making it more sparse, would improve speech recognition scores...
Widening applications of inertial sensors has triggered the search for cost effective sensors and those based on MEMS technology has been gaining popularity in particular for the lower cost applications. However, inertial sensors are subject to various error sources and characteristics of these should be modelled carefully and corrective calibration performed if these sensors are to be successfully...
In this paper, we design the optimal zero-forcing transceiver that maximizes the transmission bit rate for multiple-input multiple-output (MIMO) channels. The transmission bit rate is maximized subject to a total power constraint for a given error rate. Instead of using the same input constellation size for all subchannels as in earlier designs, the bit allocation is also taken into consideration...
In this paper, we present a new high resolution algorithm to localize multiple sources in near-field. After focusing on a pre-estimated location, the covariance matrix of the received signal is found to have the same structure as in the far-field situation, which allows the estimation of bearing with far-field subspace methods. With the estimated bearing, the range estimation of each source is consequently...
The retinal fundus photograph is widely used in the diagnosis and treatment of various eye diseases such as diabetic retinopathy and glaucoma. Medical image analysis and processing has great significance in the field of medicine, especially in non-invasive treatment and clinical study. Normally fundus images are manually graded by specially trained clinicians in a time-consuming and resource intensive...
We describe a speech enhancement system which combines a variable, input adaptive noise suppression rule with a recently developed spectral analysis framework in Hilbert domain. The variable suppression rule is an extension to a formula which encompasses well known noise reduction algorithms such as power subtraction and Wiener filtering. Time-varying parameters which are based on the input signal...
The source separation based on a statistical and computational technique is one of the most exciting topic in a multivariate signal analysis. We proposed a novel source separation technique using a tensor product expansion[1]. This technique is the signal separation that the background noise, which is observed in almost all input signals, can be estimated by using a tensor product expansion where...
In this paper, a multiple-access transmission scheme based on random permutations is studied. This scheme provides both a spectrum spreading and a time spreading, combined with a chip interleaving. One considers asynchronous transmissions on frequency-selective and time-varying channels. It is assumed that the channel coefficients are unknown by the receiver, and that only vague estimates of the minimum...
Circular features are commonly sought in digital image processing. SLIDE (Subspace based LIne DEtection) method proposed to estimate the center and the radius of a single circle by adapting array processing methods. Recently, a virtual circular array was proposed to estimate the radii of several concentric circles. A difficulty arises when intersecting circles are expected. In this paper, for the...
The Sum-squared Autocorrelation Minimization (SAM) algorithm is one technique proposed for blind adaptation of the time-domain equalizer in multicarrier systems. The SAM cost depends on the effective channel autocorrelation, which will not be changed if any TEQ zeros are flipped over the unit circle. As a consequence, the SAM cost is multimodal, and different minima may yield very different shortening...
The directional maximum (DM) technique for processing ultrasonic arc maps is proposed and compared to previously existing techniques. The method processes ultrasonic arc maps directionally to extract the map of the environment and overcome the intrinsic angular uncertainty of ultrasonic sensors. It also eliminates noise and cross-talk related misreadings successfully. The comparison is based on experimental...
In this paper we propose an iterative technique that enhances the average event related potential (ERP) by correcting the delay associated with the ERP in each trial. This correction is done in three steps: in the first step a sparse template function is estimated. In the second step, this template is utilized in estimating the inter-trial ERP delays. The ERPs fromeach trial are time-aligned using...
In this paper we investigate biometric person identification. We model this process of person identification as multiple hypothesis testing and consider performance measures that can be attained in such a protocol in terms of exponents of average error probability. A special attention is paid to the privacy related issues. In particular, we consider performance/privacy trade-off due to the indirect...
Noise robustness of automatic speech recognition benefits from using missing data imputation: Prior to recognition the parts of the spectrogram dominated by noise are replaced by clean speech estimates. Especially at low SNRs each frame contains at best only a few uncorrupted coefficients. This makes frame-by-frame restoration of corrupted feature vectors error-prone, and recognition accuracy will...
Methods for noise robust speech recognition are often evaluated in small vocabulary speech recognition tasks. In this work, we use missing feature reconstruction for noise compensation in large vocabulary continuous speech recognition task with speech data recorded in noisy environments such as cafeterias. In addition, we combine missing feature reconstruction with constrained maximum likelihood linear...
We address the problem of source separation in echoic and anechoic environments, with a new algorithm which adaptively learns a set of sparse stereo dictionary elements, which are then clustered to identify the original sources. The atom pairs learned by the algorithm are found to capture information about the direction of arrival of the source signals, which allows to determine the clusters. A similar...
This paper introduces the concept of a complementary matching pursuit for sparse approximation. The algorithm is analogous to the classical matching pursuit but done in the row-space of the dictionary matrix. A deeper analysis of the algorithm shows that the residual error at any iteration may not be orthogonal to the immediately selected atom, however, this brings about the possibility of increasing...
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