Speech Data Rate Reduction Part II: Applicability of Sensitivity and Error Analysis

This paper deals with the application of modern estimation techniques to the problem of speech data rate reduction. It is desirable to adaptively identify and quantitize the parameters of the speech model. These paramaters cannot be identified and quantized exactly; the performance of the predictor is thereby degraded and this could prevent data reduction. In many cases it is desirable to emply a suboptimal predictor in order to simplify the algorithms, and predictor performance is again degraded. This paper develops sensitivity and error analysis as a potential method for determining quantitatively how speech data reduction system performance is degraded by imprecise parameter knowledge or suboptimal filtering. An intended use of the sensitivity and error analysis algorithms is to determine parameter identification and model structure requirements of configuration concepts for adaptive speech digitizers. First, sensitivity and error analysis algorithms are presented that form the basis for the remainder of the work. The algorithms are then used to determine how imprecise knowledge of vocal tract parameters degrades predictor performance in speech. Transversal filters have previously been proposed for this application. The sensitivity analysis algorithms are then used to determine when and by how much the transverse filter is suboptimal to the Kalman filter. In particular, the question of how effectively a higher order of all-pole model approximates a system with zeros is answered, as this question is of considerable importance in speech. Finally, the physical significance of the innovations process in speech data rate reduction is studied.     

Nuclear propulsion—a historical perspective

Those who fear development of nuclear propulsion for space travel forget that considerable work on it has already been done, starting in the 1950s, and that the concept of a nuclear rocket was safely and successfully tested in the 1960s. This article describes the history of the US Nuclear Engine for Rocket Vehicle Application programme, with technical details of its development. Although funding for the programme ceased in the 1970s, there is no reason to suppose that the concept would not work today.     

Speech Data Rate Reduction Part I: Applicability of Modern Estimation Theory

Efficient coding of continuous speech signals for digital representation has attracted much interest in recent years. The underlying aim of efficient coding methods is to reduce the channel capacity required to represent a signal to meet a specific reconstruction fidelity criterion. To achieve this objective, modern speech data compression techniques rely on two very similar procedures. One procedure uses predictive deconvolution which subtracts from the current signal value that portion which can be predicted from its past and thus removes redundancy in the speech by removing sequential correlation. The signal thus requires fewer bits for equivalent quantization error. The second procedure involves identification of a complete mathematical model of the speech producing mechanism. This involves determination of the characteristics of the source that drives this transfer function. Data reduction is again achieved since the rate of change of the parameters of the speech model is much smaller than the rate of change of the speech waveform. This paper develops these data reduction procedures in terms of modern estimation theory, specifically a Kalman filter model, and illustrates the utility of this model as an analysis tool by means of an example based on a uniform tube which provides a qualitative assessment of the potential of the technique for application to real speech signals.     

Astrobiological considerations for the selection of the geological filters on the ExoMars PanCam instrument

The Panoramic Camera (PanCam) instrument will provide visible-near IR multispectral imaging of the ExoMars rover's surroundings to identify regions of interest within the nearby terrain. This multispectral capability is dependant upon the 12 preselected "geological" filters that are integrated into two wide-angle cameras. First devised by the Imager for Mars Pathfinder team to detect iron oxides, this baseline filter set has remained largely unchanged for subsequent missions (Mars Exploration Rovers, Beagle 2, Phoenix) despite the advancing knowledge of the mineralogical diversity on Mars. Therefore, the geological filters for the ExoMars PanCam will be redesigned to accommodate the astrobiology focus of ExoMars, where hydrated mineral terrains (evidence of past liquid water) will be priority targets. Here, we conduct an initial investigation into new filter wavelengths for the ExoMars PanCam and present results from tests performed on Mars analog rocks. Two new filter sets were devised: one with filters spaced every 50?nm ("F1-12") and another that utilizes a novel filter selection method based upon hydrated mineral reflectance spectra ("F2-12"). These new filter sets, along with the Beagle 2 filter set (currently the baseline for the ExoMars PanCam), were tested on their ability to identify hydrated minerals and biosignatures present in Mars analog rocks. The filter sets, with varying degrees of ability, detected the spectral features of minerals jarosite, opaline silica, alunite, nontronite, and siderite present in these rock samples. None of the filter sets, however, were able to detect fossilized biomat structures and small (<2?mm) mineralogical heterogeneities present in silica sinters. Both new filter sets outperformed the Beagle 2 filters, with F2-12 detecting the most spectral features produced by hydrated minerals and providing the best discrimination between samples. Future work involving more extensive testing on Mars analog samples that exhibit a wider range of mineralogies would be the next step in carefully evaluating the new filter sets.