On the measurement of frequency and of its sample variance with high-resolution counters

A frequency counter measures the input frequency $\bar{\nu}$ averaged over a suitable time $\tau$, versus the reference clock. High resolution is achieved by interpolating the clock signal. Further increased resolution is obtained by averaging multiple frequency measurements highly overlapped. In the presence of additive white noise or white phase noise, the square uncertainty improves from $\smash{\sigma^2_\nu\propto1/\tau^2}$ to $\smash{\sigma^2_\nu\propto1/\tau^3}$. Surprisingly, when a file of contiguous data is fed into the formula of the two-sample (Allan) variance $\smash{\sigma^2_y(\tau)=\mathbb{E}\{\frac12(\bar{y}_{k+1}-\bar{y}_k) ^2\}}$ of the fractional frequency fluctuation $y$, the result is the \emph{modified} Allan variance mod $\sigma^2_y(\tau)$. But if a sufficient number of contiguous measures are averaged in order to get a longer $\tau$ and the data are fed into the same formula, the results is the (non-modified) Allan variance. Of course interpretation mistakes are around the corner if the counter internal process is not well understood.Comment: 14 pages, 5 figures, 1 table, 18 reference

Compressed sensing with continuous parametric reconstruction

This work presents a novel unconventional method of signal reconstruction after compressive sensing. Instead of usual matrices, continuous models are used to describe both the sampling process and acquired signal. Reconstruction is performed by finding suitable values of model parameters in order to obtain the most probable fit. A continuous approach allows more precise modelling of physical sampling circuitry and signal reconstruction at arbitrary sampling rate. Application of this method is demonstrated using a wireless sensor network used for freshwater quality monitoring. Results show that the proposed method is more robust and offers stable performance when the samples are noisy or otherwise distorted

Emotion Recognition from Speech with Acoustic, Non-Linear and Wavelet-based Features Extracted in Different Acoustic Conditions

ABSTRACT: In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called "paralinguistic" aspects of the speech, including the emotions, and the personality of the speaker. This research work aims in the development of a methodology for the automatic emotion recognition from speech signals in non-controlled noise conditions. For that purpose, different sets of acoustic, non-linear, and wavelet based features are used to characterize emotions in different databases created for such purpose

Estimation Techniques and Mitigation Tools for Ionospheric effects on GNSS Receivers

Navigation is defined as the science of getting a craft or person from one place to another. The development of radio in the past century brought fort new navigation aids that enabled users, or rather their receivers, to compute their position with the help of signals from one or more radio-navigation system . The U.S. Global Positioning System (GPS) was envisioned as a satellite system for three-dimensional position and velocity determination fulfilling the following key attributes: global coverage, continuous/all weather operation, ability to serve high-dynamic platforms, and high accuracy. It represents the fruition of several technologies, which matured and came together in the second half of the 20th century. In particular, stable space-born platforms, ultra-stable atomic frequency standards, spread spectrum signaling, and microelectronics are the key developments in the realization and success of GPS. While GPS was under development, the Soviet Union undertook to develop a similar system called GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS). Both GLONASS and GPS were designed primarily for the military, but have transitioned in the past decades towards providing civilian and Safety-of-Life services as well. Other Global Navigation Satellite Systems (GNSS) are now being developed and deployed by governments, international consortia, and commercial interests. Among these are the European system Galileo and the Chinese system Beidou. Other regional systems are the Japanese Quasi-Zenith Satellite System and the Indian Gagan. GNSS have become a crucial component in countless modern systems, e.g. in telecommunication, navigation, remote sensing, precise agriculture, aviation and timing. One of the main threats to the reliable and safe operation of GNSS are the variable propagation conditions encountered by GNSS signals as they pass through the upper atmosphere of the Earth. In particular, irregular concentration of electrons in the ionosphere induce fast fluctuations in the amplitude and phase of GNSS signals called scintillations. The latter can greatly degrade the performance of GNSS receivers, with consequent economical impacts on service providers and users of high performance applications. New GNSS navigation signals and codes are expected to help mitigate such effects, although to what degree is still unknown. Furthermore, these new technologies will only come on line incrementally over the next decade as new GNSS satellites become operational. In the meantime, GPS users who need high performance navigation solution, e.g., offshore drilling companies, might be forced to postpone operations for which precision position knowledge is required until the ionospheric disturbances are over. For this reason continuous monitoring of scintillations has become a priority in order to try to predict its occurrence. Indeed, it is a growing scientific and industrial activity. However, Radio Frequency (RF) Interference from other telecommunication systems might threaten the monitoring of scintillation activity. Currently, the majority of the GNSS based application are highly exposed to unintentional or intentional interference issues. The extremely weak power of the GNSS signals, which is actually completely buried in the noise floor at the user receiver antenna level, puts interference among the external error contributions that most degrade GNSS performance. It is then of interest to study the effects these external systems may have on the estimation of ionosphere activity with GNSS. In this dissertation, we investigate the effect of propagation issues in GNSS, focusing on scintillations, interference and the joint effect of the two phenomena

Emotion recognition based on the energy distribution of plosive syllables

We usually encounter two problems during speech emotion recognition (SER): expression and perception problems, which vary considerably between speakers, languages, and sentence pronunciation. In fact, finding an optimal system that characterizes the emotions overcoming all these differences is a promising prospect. In this perspective, we considered two emotional databases: Moroccan Arabic dialect emotional database (MADED), and Ryerson audio-visual database on emotional speech and song (RAVDESS) which present notable differences in terms of type (natural/acted), and language (Arabic/English). We proposed a detection process based on 27 acoustic features extracted from consonant-vowel (CV) syllabic units: \ba, \du, \ki, \ta common to both databases. We tested two classification strategies: multiclass (all emotions combined: joy, sadness, neutral, anger) and binary (neutral vs. others, positive emotions (joy) vs. negative emotions (sadness, anger), sadness vs. anger). These strategies were tested three times: i) on MADED, ii) on RAVDESS, iii) on MADED and RAVDESS. The proposed method gave better recognition accuracy in the case of binary classification. The rates reach an average of 78% for the multi-class classification, 100% for neutral vs. other cases, 100% for the negative emotions (i.e. anger vs. sadness), and 96% for the positive vs. negative emotions

Estimation, Analysis and Smoothing of Self-Similar Network Induced Delays in Feedback Control of Nuclear Reactors

This paper analyzes a nuclear reactor power signal that suffers from network induced random delays in the shared data network while being fed-back to the Reactor Regulating System (RRS). A detailed study is carried out to investigate the self similarity of random delay dynamics due to the network traffic in shared medium. The fractionality or selfsimilarity in the network induced delay that corrupts the measured power signal coming from Self Powered Neutron Detectors (SPND) is estimated and analyzed. As any fractional order randomness is intrinsically different from conventional Gaussian kind of randomness, these delay dynamics need to be handled efficiently, before reaching the controller within the RRS. An attempt has been made to minimize the effect of the randomness in the reactor power transient data with few classes of smoothing filters. The performance measure of the smoothers with fractional order noise consideration is also investigated into.Comment: 6 pages, 6 figure

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

Novel Pitch Detection Algorithm With Application to Speech Coding

This thesis introduces a novel method for accurate pitch detection and speech segmentation, named Multi-feature, Autocorrelation (ACR) and Wavelet Technique (MAWT). MAWT uses feature extraction, and ACR applied on Linear Predictive Coding (LPC) residuals, with a wavelet-based refinement step. MAWT opens the way for a unique approach to modeling: although speech is divided into segments, the success of voicing decisions is not crucial. Experiments demonstrate the superiority of MAWT in pitch period detection accuracy over existing methods, and illustrate its advantages for speech segmentation. These advantages are more pronounced for gain-varying and transitional speech, and under noisy conditions

Wavelet based design of digital multichannel communications systems

The huge penetration of the personal communications systems in the market is constantly presenting new challenges to the research, aimed at satisfying people's needs and requirements for effective communication systems. At present, the cellular telephone network is perhaps the most evident example of communication system that has had a great impact on the lives of ordinary people and, at the same time, is the subject of interest of many researchers both at academic and industrial level. For the future, one of the main challenges in telecommunications will be the provision of ubiquitous broadband tetherless integrated services to mobile users. Such a pretentious goal cannot be achieved without a continuous research facing such problems as service quality, complete mobility support, and affordable complexity that are still open problems. However, present telecommunication problems are not only a matter of implementation or development of new services, exploiting a totally assessed doctrine. In order to respond to the mobility of the users personal communication systems have to deal with the wireless communication channel whereby mobility and non-stationarity of the propagation conditions require a stochastic description of the channel parameters. While this fact can be viewed as strong limitation to the development of a solid theory whose validity can be assesed in practice, on the other hand allows for an investigation and study of novel communication schemes, sometimes encompassing basic aspects of digital communications. This thesis, is the result of a research work that has investigated one of the basic building block of every communication systems, the modulation scheme, and the design of the pulse shape carrying the digital information. We have studied the design of multichannel communication scheme exploiting the mathematical theory of wavelets. Such a theory, developed recently, has had a great impact in many fields of engineering and of other scientific disciplines. In particular, wavelet theory has become very popular in the signal processing area; in fact it is a flexible toolbox for signal analysis allowing effective representation of signals for features extraction purposes. The main features that make wavelet waveforms suitable to be used as shaping pulses for modulation are their substantial compact support both in the time and frequency domains, and the fact that they are ISI-free pulses over frequency flat channels. The study presented in this thesis is focused on application of wavelet theory to design high-efficiency multichannel communication schemes and to the performance evaluation over linear and non-linear channels. We present a general method to design wavelet based multichannel communication schemes that we denoted Wavelet Orthogonal Frequency Division Multiplexing (WOFDM). We show that such schemes, having a largerspectral efficiency for a small number of channels, are a valid alternative to the classical OFDM. Potential advantage of wavelet modulation are shown presenting other applications examined in this thesis: a joint use of WOFDM and Trellis Coded Modulation to shape the power spectrum in order to match a frequency selective channel and minimize distortion, and application to spread spectrum modulation. Particular attention has been devoted to the timing recovery problem in multichannel communication schemes, exploiting the timing information of the different subchannels to improve the error variance in estimation of the sampling instant leading to a reduction of the adjacent channels interferenc