Improving Sparsity in Kernel Adaptive Filters Using a Unit-Norm Dictionary

Kernel adaptive filters, a class of adaptive nonlinear time-series models, are known by their ability to learn expressive autoregressive patterns from sequential data. However, for trivial monotonic signals, they struggle to perform accurate predictions and at the same time keep computational complexity within desired boundaries. This is because new observations are incorporated to the dictionary when they are far from what the algorithm has seen in the past. We propose a novel approach to kernel adaptive filtering that compares new observations against dictionary samples in terms of their unit-norm (normalised) versions, meaning that new observations that look like previous samples but have a different magnitude are not added to the dictionary. We achieve this by proposing the unit-norm Gaussian kernel and define a sparsification criterion for this novel kernel. This new methodology is validated on two real-world datasets against standard KAF in terms of the normalised mean square error and the dictionary size.Comment: Accepted at the IEEE Digital Signal Processing conference 201

Global Representation of the Fine Structure Constant and its Variation

The fine structure constant, alpha, is shown to be proportional to the ratio of the quanta of electric and magnetic flux of force of the electron, and provides a new representation, which is global across all unit systems. Consequently, a variation in alpha was shown to manifest due to a differential change in the fraction of the quanta of electric and magnetic flux of force, while a variation in hcross.c was shown to manifest due to the common mode change. The representation is discussed with respect to the running of the fine structure constant at high energies (small distances), and a putative temporal drift. It is shown that the running of the fine structure constant is due to equal components of electric screening (polarization of vacuum) and magnetic anti-screening (magnetization of vacuum), which cause the perceived quanta of electric charge to increase at small distances, while the magnetic flux quanta decreases. This introduces the concept of the bare magnetic flux quanta as well as the bare electric charge. With regards to temporal drift, it is confirmed that it is impossible to determine which fundamental constant is varying if alpha varies.Comment: Final accepted version for Metrologia. This version includes a proof that the representation of the fine structure constant is global across all unit systems, using Jackson's global representation of Maxwell's equations (which is also valid for all unit systems). The version is shorter than the previous, thus the discussion throughout is more brie

Gravitational Wave Detection with High Frequency Phonon Trapping Acoustic Cavities

There are a number of theoretical predictions for astrophysical and cosmological objects, which emit high frequency ($10^6-10^9$~Hz) Gravitation Waves (GW) or contribute somehow to the stochastic high frequency GW background. Here we propose a new sensitive detector in this frequency band, which is based on existing cryogenic ultra-high quality factor quartz Bulk Acoustic Wave cavity technology, coupled to near-quantum-limited SQUID amplifiers at $20$~mK. We show that spectral strain sensitivities reaching $10^{-22}$ per $\sqrt{\text{Hz}}$ per mode is possible, which in principle can cover the frequency range with multiple ($>100$) modes with quality factors varying between $10^6-10^{10}$ allowing wide bandwidth detection. Due to its compactness and well established manufacturing process, the system is easily scalable into arrays and distributed networks that can also impact the overall sensitivity and introduce coincidence analysis to ensure no false detections.Comment: appears in Phys. Rev. D, (2014