SiO2 coating of silver nanoparticles by photoinduced chemical vapor deposition.

Gas-phase silver nanoparticles were coated with silicon dioxide (SiO2) by photoinduced chemical vapor deposition (photo-CVD). Silver nanoparticles, produced by inert gas condensation, and a SiO2 precursor, tetraethylorthosilicate (TEOS), were exposed to vacuum ultraviolet (VUV) radiation at atmospheric pressure and varying temperatures. The VUV photons dissociate the TEOS precursor, initiating a chemical reaction that forms SiO2 coatings on the particle surfaces. Coating thicknesses were measured for a variety of operation parameters using tandem differential mobility analysis and transmission electron microscopy. The chemical composition of the particle coatings was analyzed using energy dispersive x-ray spectrometry and Fourier transform infrared spectroscopy. The highest purity films were produced at 300-400 degrees C with low flow rates of additional oxygen. The photo-CVD coating technique was shown to effectively coat nanoparticles and limit core particle agglomeration at concentrations up to 10(7) particles cm(-3).

The estimation of stochastic context-free grammars using the Inside-Outside algorithm

Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.

PARTIALLY COHERENT DYNAMIC PROGRAMMING ALGORITHM FOR CPM DETECTION.

A dynamic programming algorithm for joint data detection and carrier phase estimation of continuous-phase-modulated signal is presented. The intent is to combine the robustness of noncoherent detectors with the superior performance of coherent ones. The algorithm differs from the Viterbi algorithm only in the metric that it maximizes over the possible transmitted data sequences. This metric is influenced both by the correlation with the received signal and the current estimate of the carrier phase. Carrier-phase estimation is based on decision guiding, but there is no external phase-locked loop. Instead, the phase of the best complex correlation with the received signal over the last few signaling intervals is used. The algorithm is slightly more complex than the coherent Viterbi algorithm but does not require narrowband filtering of the recovered carrier, as earlier appproaches did, to achieve the same level of performance.

Applications of stochastic context-free grammars using the Inside-Outside algorithm

This paper describes two applications in speech recognition of the use of stochastic context-free grammars (SCFGs) trained automatically via the Inside-Outside Algorithm. First, SCFGs are used to model VQ encoded speech for isolated word recognition and are compared directly to HMMs used for the same task. It is shown that SCFGs can model this low-level VQ data accurately and that a regular grammar based pre-training algorithm is effective both for reducing training time and obtaining robust solutions. Second, an SCFG is inferred from a transcription of the speech used to train a phoneme-based recognizer in an attempt to model phonotactic constraints. When used as a language model, this SCFG gives improved performance over a comparable regular grammar or bigram. © 1991.