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In recent years a number of novel distributed parameter estimation algorithms have been developed stimulated by applications in cognitive radio, robotics, wireless networks and sensor networks. However, existing performance analyses have used white noise assumptions extensively. Here, we analyse for the first time a class of diffusion LMS strategies under autocorrelation assumptions. Further, we obtain...
Image registration technology is getting more and more important in nowadays. The accuracy of the registration resolution plays an important. In this passage, we present an image registration algorithm based on point feature of sub-pixel, which can improve the accuracy. Firstly we use Harris corner point algorithm to get point features, then we use our method to refine the Harris points, after that...
An algorithm for synchronization of a decoder of a RFID receiver has been proposed, implemented and evaluated, by experimental setup. The solution can be used for UHF RFID (e.g. ISO18000-6 and EPC gen 2) readers using FM0, bi-phase or differential Manchester decoding. Goal of the proposed solution is the improved decoding of the received data in the presence of noise (so by using less power or working...
In many real-world networks, interactions between entities are observed at specific moments in continuous time, such as email, SMS messaging, and IP traffic. The majority of methods for analyzing such data first aggregate communication over designated time blocks, resulting in one or more discrete time series, to which existing tools can be applied. However, regardless of how the block lengths are...
This paper considers the problem of tracking a dynamic sparse channel in a broadband wireless communication system. A probabilistic signal model is firstly proposed to describe the special features of temporal correlations of dynamic sparse channels: path delays change slowly over time, while path gains evolve faster. Based on such temporal correlations, we then propose the differential orthogonal...
Singing Voice Separation (SVS) is a task which uses audio source separation methods to isolate the vocal component from the background accompaniment for a song mix. This paper discusses the methods of evaluating SVS algorithms, and determines how the current state of the art measures correlate to human perception. A modified ITU-R BS.1543 MUSHRA test is used to get the human perceptual ratings for...
In this paper, we propose a novel user clustering algorithm for non-orthogonal multiple access (NOMA) considering the channel correlation between users and the channel gain. We also adopt sum-rate maximization approach to find an optimal precoding matrix in the multi-user multiple-input-multiple-output (MU-MIMO) setup after the user clustering. Grouping two users in a single beam to serve users in...
Purpose of this paper is to present a computerized way to evaluate CTG recordings, and more specifically use of feature clustering for the classification process. We used a database which contained 552 records and 20 features. Matlab (version R2012a) was used for the experiments. First we performed a reduction of the number of features used in order to end up only with the most useful ones. That set...
The Steered Response Power using the Phase Transform weight (SRP-PHAT) has been shown to be robust in noisy and reverberant conditions. Also, volume contraction has been applied effectively to trap the global maximum for densely-hilly 3-D spaces like the SRP. However, previous methods have suffered from the presence of peaks representing multiple talkers in close proximity as is likely in a conversational...
Signal detection and RF parameter estimation have received great interest in recent years due to the need for spectrum sensing in rapidly growing cognitive radio and cyber security research. In most conventional signal detection and RF parameter estimation work, the target signal is often assumed to be a single primary user signal without overlap in spectrum with other signals. However, in a spectrally...
In view of the Beidou satellite signal acquisition takes up hardware resources and consumes time, double-stages compression sensing acquire method is putted forward combined with the advantages of compressed sensing in data mining. The sparsity of Beidou signal in correlation domain is used to structure transformation matrix while the Walsh-Hadamard matrix was used to reconstruct signal. The method...
The main aim of the biomedical signal processing is to extract information from a biological signal. Biomedical signal processing involves recording of the biological events such as heart-beats etc. The feasibility of extracting accurate Heart-Rate is demonstrated by measuring the variability in the photoelectric plethysmography signals. The Pulse Rate is obtained from the systolic peaks of the pulse...
The reliability of spectrum sensing is a challenging issue in cognitive radio (CR) systems. In this paper, we validate the reliability of two spectrum sensing algorithms for pilot-added OFDM signals: time-domain symbol cross-correlation (TDSC) and periodical peaks of autocorrelation (PPA) with a real system in real environments. To validate, these two algorithms carry out detection function for real...
The electrical activity signals in plants can provide useful information to monitor environmental conditions, such as atmospheric pollution. Nonetheless the study of the relationship between environmental stimuli and electrical responses of plants is still a critical step in developing technologies that use plants as organic sensing devices. In this paper an automatic method of analysis of plant electrical...
In cognitive radio networks, the task of spectrum sensing is required to be reliable at low signal-to-noise ratios (SNRs). Spectral correlation is an effective approach to satisfy the requirement. The algorithms based on statistic spectral correlation profiles are a good method as shown in some previous works. In this paper, we propose an algorithm with maximum ratio combination for the profiles to...
This paper describes a polyphonic multi-pitch detector which selects peaks as pitch candidates in both the spectrum and a multi-channel generalised autocorrelation. A final pitch is detected if a peak in the spectrum has a corresponding peak within the same semitone range in at least one of the autocorrelation channels. The autocorrelation is calculated in octave bands and all pre-processing steps...
Adaptive feedback cancellation (AFC) algorithms are used to solve the problem of acoustic feedback, but, frequently, they do not address the fundamental problem of loudspeaker and source signal correlation, leading to an estimation bias if standard adaptive filtering methods are used. Loudspeaker and source signal prefiltering via the prediction-error method (PEM) can address this problem. In addition...
This paper considers the scenario when a mix of signals from multiple acoustic sources is received by a microphone array. The problem is to estimate the waveform of the source of interest located in the near field of the array. The considered problem can arise in many applications such as video conferencing, acoustic room surveillance and others, when it is necessary to capture human speech against...
In Compressed Sensing, a real-valued sparse vector has to be reconstructed from an underdetermined system of linear equations. However, in many applications of digital communications the elements of the unknown sparse vector are drawn from a finite set. The standard reconstruction algorithms of Compressed Sensing do not take this knowledge into account, hence, enhanced algorithms are required to achieve...
A heterogeneous Software Defined Radio (SDR) cluster platform that handles highly demanding processing algorithms in real-time is proposed. The solution based on a combination of FPGA, GPU and CPU offers the best balance between performance, cost, and flexibility. The key feature of our heterogeneous platform is achieving the required performance by assigning the tasks according to the technology...
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