Correction to: Matrix spectral factorization for SA4 multiwavelet

Multidimensional Systems and Signal Processing - After a careful review of the published version of our paper, we discovered that some references to the number of multiwavelet decomposition and...     

Wavelets and differential-dilation equations

It is shown how differential-dilation equations can be constructed using iterations, similar to the iterations with which wavelets and dilation equations are constructed. A continuous-time wavelet is constructed starting from a differential-dilation equation. It has compact support and excellent time domain and frequency domain localization properties. The wavelet is infinitely differentiable and therefore cannot be obtained using digital filter banks. In addition, the wavelet has excellent approximation properties. New sampling and differentiation techniques are also introduced. Results on image interpolation using the solution of the differential-dilation equation are presented. Examples are given, demonstrating the suitability of the new wavelet function for signal analysis     

Multidimensional Two-channel Linear Phase FIR Filter Banks and Wavelet Bases with Vanishing Moments

In the paper new design methods for multidimensional two-channel perfect reconstruction (PR) FIR filter banks are described. The filters have linear phase, achieve an arbitrarily high number of vanishing moments and can be used to obtain biorthogonal wavelet bases. Two-dimensional wavelet bases with square, rectangular, and hexagonal support are constructed. A design method that trades off vanishing moments and frequency selectivity is described. These two properties are both important in subband coding, but they each require a share of the degrees of freedom available from the total number of filter coefficients. Novel analytic formulae are derived and are applied to provide illustrative examples.     

Long-Term Spectrum Monitoring with Big Data Analysis and Machine Learning for Cloud-Based Radio Access Networks

Spectrum monitoring is important for efficient spectrum sharing and resource management in cloud-based radio access networks (C-RAN). In this paper we show how data obtained from long-term spectrum monitoring together with machine learning (ML) operating on big data (BD) can be used in a C-RAN scenario for spectrum management purposes. We propose an approach for spectrum occupancy forecasting which can be used to reduce the delay in making dynamic spectrum allocation decisions and improve the cognitive and management functionalities of cloud-based architectures such as C-RAN. The spectrum occupancy and usage activity in a predefined frequency band is based on the statistical processing of a large amount of collected data and the introduction of a frequency–time resources indicator as a measure of spectrum usage. Furthermore, we apply ML algorithms to predict spectrum usage and compare the predicted with actual measured data. Taking into consideration that the accuracy of the prediction depends on the volume of collected data and the time of prediction on the BD and ML approach, we propose the development of a cloud-based generic processing architecture to solve the “accuracy versus latency” trade-off problem. The proposed architecture is appropriate for deployment in cognitive C-RAN.     

Robust image watermarking using non-regular wavelets

An approach to watermarking digital images using non-regular wavelets is advanced. Non-regular transforms spread the energy in the transform domain. The proposed method leads at the same time to increased image quality and increased robustness with respect to lossy compression. The approach provides robust watermarking by suitably creating watermarked messages that have energy compaction and frequency spreading. Our experimental results show that the application of non-regular wavelets, instead of regular ones, can furnish a superior robust watermarking scheme. The generated watermarked data is more immune against non-intentional JPEG and JPEG2000 attacks.     

Matrix spectral factorization for SA4 multiwavelet

Multidimensional Systems and Signal Processing - In this paper, we investigate Bauer’s method for the matrix spectral factorization of an r-channel matrix product filter which is a half-band...     

An Implementation of IEEE 1588 Over IEEE 802.11b for Synchronization of Wireless Local Area Network Nodes

IEEE 1588 is a new standard to synchronize independent clocks running on separate nodes of a distributed measurement and control system. It is intended for high-accuracy implementations on compact systems such as a single subnet. This paper examines potential accuracy limitations introduced by the physical layer of the IEEE 802.11b wireless local area network. Experimental results are presented that show that these limitations do not preclude clock-synchronization accuracy of several hundred nanoseconds.     

The coding of image sequences by wavelets, wavelet packets andother subband coding schemes

For the terrestrial broadcasting of high-definition television (HDTV) in North America the discrete cosine transform (DCT), Huffman (lossless) coding and motion detection, estimation and compensation have been used to compress raw HDTV rates of 1.0-1.2 Gbps. Compressed and compacted video bit rates range from 12.59 Mbps to 13.60 Mbps for 16-QAM transmission and from 17.47 to 18.88 for 32-QAM transmission. MPEG source coding schemes, are used in a proposed HDTV system and in the Grand Alliance proposal. They share features in common with other source coding schemes which have been employed. It seems likely that compression and compaction to an HDTV video bit rate below 10 Mbps should be attainable. The methods discussed in this paper provide hope for realizing this goal