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An Android-based eModule app has been designed and developed for science, technology, engineering, and mathematics (STEM) education. The eModule consists of: (1) an Android demonstration of echolocation; (2) a set of notes describing the functionality of the app, the basics of echolocation, and its application to advanced signal processing systems such as RADAR, LIDAR, and SONAR; (3) quizzes to test...
Zero crossing data contain information of a process in compact form and is therefore of interest in wireless sensor networks where only reduced amounts of data can be transmitted. When analyzing the properties of certain algorithms using zero crossing data, the cross-covariance between the zero crossing rates of two jointly Gaussian and stationary processes is needed. The evaluation of such a cross-covariance...
Neurons in the brain from connection hence many neuron together tie up to form a network. Connectivity map interprets such connections in graphical form. Various signal processing and information theory techniques, can be implemented to form connectivity of the network of neurons on the Multi electrode array dish. The time of spike occurrences and electrode location of spike were recorded from the...
Functional Magnetic Resonance Imaging (fMRI) has been valuable to the current understanding of brain function and pre-operative evaluation of patients. In the recent years, the technique has been increasingly applied to the cases when the subject is at rest, also referred to as the resting-state fMRI. Resting-state fMRI measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal...
Brain Functional Networks (BFNs), graph theoretical models of brain activity data, provide a systems perspective of complex functional connectivity within the brain. Neurological disorders are known to have basis in abnormal functional activities that could be captured in terms of network markers. Schizophrenia is a pathological condition characterized with altered brain functional state. We created...
In this paper, we aimed to get the trends of the KANSEI, which is alike “how to feel”, values of the memorable TV commercials (CMs) using the electroencephalogram (EEG) while subjects watch TV CMs. KANSEI is Japanese word because of studying at first in Japan. The questionnaire has been used as conventional evaluation method of TV CMs. This method is subjective evaluation, so it is difficult to know...
Spread spectrum communication systems can require significant computation to perform initial acquisition, searching across time and frequency to accurately detect and lock onto the desired signal. This initial acquisition problem is exacerbated in deeply spread non-binary signals lacking cyclostationary features or repetitive codes, leading to a desire for less computationally intensive approaches...
As for nonstationary signal, such as subpixel peak detection,we could be difficult to suppress the noise of super- Gaussian and sub-Gaussian in the mixed signal with the traditional low order filter. The gradient search method is generally adopt in the filter algorithm based on higher order statistics, but it is difficult to avoid local convergence and large complexity in the gradient search process...
An Android app has been developed to assist in the education of individuals in a science, technology, engineering, and mathematics (STEM) course of study. The Android Reflection Application provides students a means to determine distances to objects while allowing them the ability to manipulate signal envelopes, signal shapes, signal types, and frequency constraints. The convenient and intuitive graphical...
With the increase of multi media technology and internet there is a rapid growth in storing and retrieving of documents. Government has taken several methods for documents to scan and stored digitally for future use. Even though the documents are available in the digital format, but it is very difficult to search for a single word or phrase. Traditional optical character recognition techniques (OCR)...
Here we introduce some new linear dependence measures, namely the generalized covariation coefficient, generalized symmetric covariation coefficient and the generalized sign symmetric covariation coefficient. These measures can be applied for random variables which fulfill a certain linearity property and have finite first moments. Some basic mathematical properties of these measures are discussed...
To solve the mode mixing problem of local mean decomposition (LMD), hereby a de-correlation improved LMD algorithm was proposed. If the multi-components signal includes two signal components with similar frequency, LMD will produce mode mixing which has serious impact on signal feature extraction and subsequent time frequency analysis. The essence of the mode mixing is that the information of product...
This article concerns an autocorrelation algorithm for determining a pulse wave delay. The pulse wave delay is defined as difference between the characteristic points i.e. the difference between the R wave in the electrocardiogram signal (ECG) and distinctive point in the photoplethysmogram (PPG) waveform. Obtaining values of the characteristic points (time stamps) are realized by correlation function...
this paper presents an objective evaluation of state-of-the-art single channel noise reduction algorithms. The evaluation is performed on a representative real data set of underwater acoustic records. Rationales used to process the proposed evaluation are mean squared error, global signal-to-noise ratio (SNR), segmental SNR and mean squared spectral error. Moreover, this first quantitative evaluation...
We develop a new efficient method for designing unimodular waveforms with good auto- and cross-correlation properties for multiple-input multiple-output (MIMO) radar. Our waveform design scheme is conducted based on minimization of the integrated sidelobe level of designed waveforms, which is formulated as a quartic non-convex optimization problem. We start from simplifying the quartic optimization...
This paper presents a detection scheme for determining the number of signals that are correlated across multiple data sets when the sample size is small compared to the dimensions of the data sets. To accommodate the sample-poor regime, we decouple the problem into several independent two-channel order-estimation problems that may be solved separately by a combination of principal component analysis...
In this paper, we deal with the classification of Greek folk songs into 8 classes associated with the region of origin of the songs. Motivated by the way the sound is perceived by the human auditory system, auditory cortical representations are extracted from the music recordings. Moreover, deep canonical correlation analysis (DCCA) is applied to the auditory cortical representations for dimensionality...
Renormalized maximum likelihood (RNML) is a powerful concept from information theory. We show how it can be used to derive a criterion for selecting the order of vector autoregressive (VAR) processes. We prove that RNML criterion is strongly consistent. We also demonstrate empirically its good performance for examples of VAR which have been considered in recent literature because they possess a particular...
In this work we consider a two-channel passive detection problem, in which there is a surveillance array where the presence/absence of a target signal is to be detected, and a reference array that provides a noise-contaminated version of the target signal. We assume that the transmitted signal is an unknown rank-one signal, and that the noises are uncorrelated between the two channels, but each one...
In room acoustics, the under-modelled blind system identification (BSI) problem arises when the identified room impulse response (RIR) is shorter than the real one. Conventional BSI methods can perform poorly under these circumstances. In this paper, we propose an algorithm for multichannel BSI in under-modelled situations. Instead of minimizing the cross-relation error, a new optimization criterion...
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