On the relation of slow feature analysis and Laplacian eigenmaps

The past decade has seen a rise of interest in Laplacian eigenmaps (LEMs) for nonlinear dimensionality reduction. LEMs have been used in spectral clustering, in semisupervised learning, and for providing efficient state representations for reinforcement learning. Here, we show that LEMs are closely related to slow feature analysis (SFA), a biologically inspired, unsupervised learning algorithm originally designed for learning invariant visual representations. We show that SFA can be interpreted as a function approximation of LEMs, where the topological neighborhoods required for LEMs are implicitly defined by the temporal structure of the data. Based on this relation, we propose a generalization of SFA to arbitrary neighborhood relations and demonstrate its applicability for spectral clustering. Finally, we review previous work with the goal of providing a unifying view on SFA and LEMs. © 2011 Massachusetts Institute of Technology.

A theory of slow feature analysis for transformation-based input signals with an application to complex cells

We develop a group-theoretical analysis of slow feature analysis for the case where the input data are generated by applying a set of continuous transformations to static templates. As an application of the theory, we analytically derive nonlinear visual receptive fields and show that their optimal stimuli, as well as the orientation and frequency tuning, are in good agreement with previous simulations of complex cells in primary visual cortex (Berkes and Wiskott, 2005). The theory suggests that side and end stopping can be interpreted as a weak breaking of translation invariance. Direction selectivity is also discussed. © 2011 Massachusetts Institute of Technology.

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

Locally oxidized silicon surface-plasmon Schottky detector for telecom regime.

We experimentally demonstrate an on-chip nanoscale silicon surface-plasmon Schottky photodetector based on internal photoemission process and operating at telecom wavelengths. The device is fabricated using a self-aligned approach of local-oxidation of silicon (LOCOS) on silicon on insulator substrate, which provides compatibility with standard complementary metal-oxide semiconductor technology and enables the realization of the photodetector and low-loss bus photonic waveguide at the same fabrication step. Additionally, LOCOS technique allows avoiding lateral misalignment between the silicon surface and the metal layer to form a nanoscale Schottky contact. The fabricated devices showed enhanced detection capability for shorter wavelengths that is attributed to increased probability of the internal photoemission process. We found the responsivity of the nanodetector to be 0.25 and 13.3 mA/W for incident optical wavelengths of 1.55 and 1.31 μm, respectively. The presented device can be integrated with other nanophotonic and nanoplasmonic structures for the realization of monolithic opto-electronic circuitry on-chip.

Silicon-metal waveguide as a high efficiency Schottky detector for telecom wavelengths

We demonstrate an integrated on-chip compact and high efficiency Schottky detector for telecom wavelengths based on silicon metal waveguide. Detection is based on the internal photoemission process. Theory and experimental results are discussed. © 2012 OSA.

On chip plasmonic enhanced silicon Schottky detector for telecom wavelengths

We demonstrate an integrated on-chip plasmonic enhanced Schottky detector for telecom wavelengths based on the internal photoemission process. This CMOS compatible device may serve as a promising alternative to the Si-Ge detectors. © 2012 OSA.

Locally-oxidized silicon surface-plasmon Schottky detector for telecom wavelengths

We demonstrate an integrated on-chip locally-oxidized silicon surface-plasmon Schottky detector for telecom wavelengths based on the internal photoemission process. Theoretical model and experimental results will be presented and discussed. © 2011 IEEE.

Locally oxidized silicon surface-plasmon Schottky detector for telecom regime

We experimentally demonstrate an on-chip nanoscale silicon surface-plasmon Schottky photodetector based on internal photoemission process and operating at telecom wavelengths. The device is fabricated using a self-aligned approach of local-oxidation of silicon (LOCOS) on silicon on insulator substrate, which provides compatibility with standard complementary metal-oxide semiconductor technology and enables the realization of the photodetector and low-loss bus photonic waveguide at the same fabrication step. Additionally, LOCOS technique allows avoiding lateral misalignment between the silicon surface and the metal layer to form a nanoscale Schottky contact. The fabricated devices showed enhanced detection capability for shorter wavelengths that is attributed to increased probability of the internal photoemission process. We found the responsivity of the nanodetector to be 0.25 and 13.3 mA/W for incident optical wavelengths of 1.55 and 1.31 μm, respectively. The presented device can be integrated with other nanophotonic and nanoplasmonic structures for the realization of monolithic opto-electronic circuitry on-chip. © 2011 American Chemical Society.

Highly efficient detector of the neurotransmitter ACh and AChE inhibitors

Among the variety of applications for biosensors one of the exciting frontiers is to utilize those devices as post-synaptic sensing elements in chemical coupling between neurons and solid-state systems. The first necessary step to attain this challenge is to realize highly efficient detector for neurotransmitter acetylcholine (ACh). Herein, we demonstrate that the combination of floating gate configuration of ion-sensitive field effect transistor (ISFET) together with diluted covalent anchoring of enzyme acetylcholinesterase (AChE) onto device sensing area reveals a remarkable improvement of a four orders of magnitude in dose response to ACh. This high range sensitivity in addition to the benefits of peculiar microelectronic design show, that the presented hybrid provides a competent platform for assembly of artificial chemical synapse junction. Furthermore, our system exhibits clear response to eserine, a competitive inhibitor of AChE, and therefore it can be implemented as an effective sensor of pharmacological reagents, organophosphates, and nerve gases as well. © 2007 Materials Research Society.