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Acoustic impulse responses (IRs) are widely used to model sound propagation between two points in space. Being a point-to-point description, IRs are generally estimated based on input-output pairs for source and sensor positions of interest. Alternatively, the IR at an arbitrary location in space may be constructed based on interpolation techniques, thus alleviating the need of densely sampling th
The authors propose a computationally efficient approach to estimate the directions of arrival of far-field sources impinging on a sensor array. The proposed estimator is formed using a sparse reconstruction framework, employing a novel adaptive grid selection technique to reduce the dimensionality of the used dictionary matrix. The method further makes use of a SPICE-inspired dictionary to adapti
In this paper, we considered the real-time modeling of an underwater channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development in the modeling of acoustic channels using a Kronecker structure, we approximated the CIR using a structured and sparse model, allowing for a computationally efficient sparse block-updating algorithm
The identification of nonlinear chirp signals has attracted notable attention in the recent literature, including estimators such as the variational mode decomposition and the nonlinear chirp mode estimator. However, most presented methods fail to process signals with close frequency intervals or depend on user-determined parameters that are often non-trivial to select optimally. In this work, we
Recent advances have shown that sound fields can be accurately interpolated between microphone measurements when the spatial covariance matrix is known. This matrix may be estimated in various ways; one promising approach is to use a plane wave formulation with sparse priors, although this may require the use of a many microphones to suppress the noise. To overcome this, we introduce a time domain
The polar format algorithm (PFA) is a popular choice for general bistatic synthetic aperture radar (BiSAR) imaging due to its computational efficiency and adaptability to situations with complicated geometries or arbitrary flight trajectories. However, efficient and accurate compensation of 2-D residual phase errors induced by the wavefront curvature remains challenging when obtaining high-quality
This work is concerned with determining optimal sensor placements that allow for an accurate location estimate of structured signal sources, taking into account the expected location areas and the typical range of the parameters detailing the signals. In the presentation, we illustrate the technique for tonal sound signals, exploiting the expected harmonic structure of such signals. To determine p
In this paper we present the differentiable log-Mel spectrogram (DMEL) for audio classification. DMEL uses a Gaussian window, with a window length that can be jointly optimized with the neural network. DMEL is used as the input layer in different neural networks and evaluated on standard audio datasets. We show that DMEL achieves a higher average test accuracy for sub-optimal initial choices of th
Many forms of small-size radars suffer from minor clock oscillations due to crystalline impurities in their internal clocks, causing time-varying clock offsets between the transmitter and the receivers. This offset causes a bias and an increased variance in the positioning of close-range targets, limiting the achievable accuracy well beyond the expected estimation limitations. This performance is
This paper develops an adaptive grid two-dimensional (2-D) direction-of-arrival (DOA) estimation technique employing an integrated dictionary framework. In contrast to using a traditional grid over distinct angles, combined angle information atoms are adopted to construct the dictionary, using a SPICE-based noise power estimate to select the active regions. To compensate for off-grid bias effects,
Post-marketing reports of suspected adverse drug reactions are important for establishing the safety profile of a medicinal product. However, a high influx of reports poses a challenge for regulatory authorities as a delay in identification of previously unknown adverse drug reactions can potentially be harmful to patients. In this study, we use natural language processing (NLP) to predict whether
In order to allow for a computationally efficient estimation of radar reflections, one commonly assumes the reflecting target to be in the far-field of the sensing array, such that the impinging wavefront is modeled as a linear phase-shift along the array. This works well in most radar scenarios, but causes significant performance degradation for close-range radar systems, wherein the curvature of
Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prio
Recently, many forms of audio industrial applications, such as sound monitoring and source localization, have begun exploiting smart multi-modal devices equipped with a microphone array. Regrettably, model-based methods are often difficult to employ for such devices due to their high computational complexity, as well as the difficulty of appropriately selecting the user-determined parameters. As a
Current literature show that frequency diverse arrays (FDAs) are able of producing range–angle-dependent and time-variant transmit beampatterns, but the resulting time and range dependencies and their characteristics are still not well understood. This paper examines the FDA transmission model with an emphasis on analyzing the beam auto-scanning characteristics and the equivalence with the MIMO be
This technical report gives an overview of our submission to task 3 of the DCASE 2024 challenge. We present a sound event localization and detection (SELD) system using input features based on trainable neural generalized cross-correlations with phase transform (NGCC-PHAT). With these features together with spectrograms as input to a Transformer-based network, we achieve significant improvements o
I kapitlet beskrivs grundläggande begrepp inom behaviouristisk inlärningsteori och kognitiv personlighetsteori. Fokus läggs på de teorier som haft störst praktisk betydelse genom att de ligger till grund för olika former av kognitiv terapi och beteendeterapi. Till de begrepp som behandlas hör: respondent och operant beteende, positiv och negativ förstärkning, modellinlärning, automatiska tankar, k
In computer-vision feature extraction algorithms, compressing the image into a sparse set of trackable keypoints, empowers navigation-critical systems such as Simultaneous Localization And Mapping (SLAM) in autonomous robots, and also other applications such as augmented reality and 3D reconstruction. Most of those applications are performed in battery-powered gadgets featuring in common a very st
Migratory routes and remote wintering quarters in birds are often species and even population specific. It has been known for decades that songbirds mainly migrate solitarily, and that the migration direction is genetically controlled. Yet, the underlying genetic mechanisms remain unknown. To investigate the genetic basis of migration direction, we track genotyped willow warblers Phylloscopus troc
Many forms of bioimage analysis involve the detection of objects and their outlines. In the context of microscopy-based high-throughput drug and genomic screening and even in smaller scale microscopy experiments, the objects that most often need to be detected are cells. In order to develop and benchmark algorithms and neural networks that can perform this task, high-quality datasets with annotate
