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Applicants are invited for two Early Stage Researchers (ESR) of EU Marie Sklodowska-Curie Actions (MSCA) to be hosted in the Istituto Italiano di Tecnologia (IIT). The positions are for a fixed-term of 3 years and the successful applicants are expected to register for PhD at the University of Ferrara, in Translational Neurosciences and Neurotechnologies. The two Early Stage Researchers (ESR) of COBRA H2020 project (G.A. N.

Institute of Electronics and Computer Science (EDI) announces the opening of the competition for preliminary selection of postdoctoral applications for submission to the State Education Development Agency (SEDA) under the Activity 1.1.1.2 “Post-doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Programme “Growth and Employment”.

Section: Community & Involvement

Technical Committee Past Members   The following lists all the past chairs and members of the SPS Signal Processing Theory and Methods Technical Committee. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

We consider the problem of reliable information propagation in the brain using biologically realistic models of spiking neurons. Biological neurons use action potentials, or spikes, to encode information. Information can be encoded by the rate of asynchronous spikes or by the (precise) timing of synchronous spikes. Reliable propagation of synchronous spikes is well understood in neuroscience and is relatively easy to implement by biologically-realistic models of neurons. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Visual food recognition on mobile devices has attracted increasing attention in recent years due to its roles in individual diet monitoring and social health management and analysis. Existing visual food recognition approaches usually use large server-based networks to achieve high accuracy. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

This paper presents a novel approach for accurate barcodes detection in real and challenging environments using compact deep neural networks. Our approach is based on Convolutional Neural Network ( CNN ) and neural network compression, which can detect the four vertexes coordinates of a barcode accurately and quickly. Our approach consists of four stages: ( i ) feature extraction by a base network, ( ii ) region proposal network ( RPN ) training, ( iii ) barcode classification and coordinates regression, and ( iv ) weights pruning and recoding.

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Previous research methods on wake-up word detection (WWD) have been proposed with focus on finding a decent word representation that can well express the characteristics of a word. However, there are various obstacles such as noise and reverberation which make it difficult in real-world environments where WWD works.

Section: Publications & Resources

Publication: IEEE Signal Processing Letters

Automatic modulation classification facilitates many important signal processing applications. Recently, deep learning models have been adopted in modulation recognition, which outperform traditional machine learning techniques based on hand-crafted features. However, automatic modulation classification is still challenging due to the following reasons.

Section: Publications & Resources

Publication: IEEE Transactions on Audio, Speech and Language Processing

The filtered-x least-mean-square (FxLMS) algorithm has been widely used for the active noise control. A fundamental analysis of the convergence behavior of the FxLMS algorithm, including the transient and steady-state performance, could provide some new insights into the algorithm and can be also helpful for its practical applications, e.g., the choice of the step size.

Section: Publications & Resources

Publication: IEEE Transactions on Audio, Speech and Language Processing

This paper presents a robust beamformer for stereo noise reduction in hearing aid applications. The worst-case optimization method was applied to the binaural minimum-variance distortionless-response (BMVDR) beamformer, for providing robustness against parameter estimation inaccuracies.