Lag-windowing and multiple-data-windowing are roughly equivalent for smooth spectrum estimation

There is no fundamental difference between lag-windowing a correlation sequence and multiple-windowing a data sequence when the objective is to reduce the mean-squared error of a spectrum estimator. By analyzing the approximate low-rank factorization of a bandlimiting Toeplitz operator, we find that lag-windowed (or spectrally smoothed) spectrum estimators have multiple-data-windowed implementations. This makes the Blackman-Tukey-Grenander-Rosenblatt spectrogram equivalent to the Thomson spectrum estimator (and vice-versa), meaning BTGR spectrograms may be implemented in a multichannel filterbank version of the Thomson estimator.     

Development of pulmonary hypertension after lung volume reduction surgery

This prospective, longitudinal study was designed to assess the hemodynamic changes occurring in patients who undergo lung volume reduction surgery (LVRS). Patients with emphysema treated with LVRS underwent hemodynamic evaluation before and after surgery. The study group consisted of nine patients with an average age of 64.4 yr. FEV1 rose significantly from 0.64 preoperatively to 0.99 L postoperatively. After surgery, pulmonary artery (PA) systolic pressure rose to 47.9 +/- 12.4 mm Hg, meeting criteria for development of pulmonary hypertension. In six patients, the elevation in PA pressure was attributed to an increase in the pulmonary vascular resistance, but for all nine patients the change was not statistically significant. The pulmonary artery occulsion pressure (PAOP) did not change postoperatively. There was no correlation of PAOP with global left ventricular ejection fraction. While preoperatively there was a negative correlation between symptoms (Mahler dyspnea index) and PA pressure, after surgery the change in PA pressures did not correlate with the change in symptoms (Mahler transitional dyspnea index). We concluded that development of pulmonary hypertension may occur after LVRS in patients whose symptomatic status improves and in whom this condition was not present preoperatively.     

Detection and estimation of improper complex random signals

Nonstationary complex random signals are in general improper (not circularly symmetric), which means that their complementary covariance is nonzero. Since the Karhunen-Loeve (K-L) expansion in its known form is only valid for proper processes, we derive the improper version of this expansion. It produces two sets of eigenvalues and improper observable coordinates. We then use the K-L expansion to solve the problems of detection and estimation of improper complex random signals in additive white Gaussian noise. We derive a general result comparing the performance of conventional processing, which ignores complementary covariances, with processing that takes these into account. In particular, for the detection and estimation problems considered, we find that the performance gain, as measured by deflection and mean-squared error (MSE), respectively, can be as large as a factor of 2. In a communications example, we show how this finding generalizes the result that coherent processing enjoys a 3-dB gain over noncoherent processing.     

A unified framework for the Sussman, Moyal, and Janssen formulas

This paper derives three fundamental identities in the radar and sonar literature, namely, Sussman' identity for ambiguity functions, Moyal's formula which establishes the value of the inner product between two scattering functions, and Janseen's formula which establishes identities for mixed inner products between waveforms and Gabor wavelets. Starting from the fundamental convolution identity, we derive Sussman's identity. Following from an initial value theorem of Fourier analysis, we obtained Moyal's formula. Following from Poisson's sum formula and an initial value theorem, we also obtained Janssen's equality. The relationship between these three identities is as follows: Janssen's formula is a sampled-data version of Moyal's formula, and both follow from Sussman's identity. In turn, Sussman's identity is a consequence of the fundamental convolution identity.     

Effects of buried layer geometry on characteristics of doublepolysilicon bipolar transistors

Dependences of electrical characteristics of double polysilicon transistors on n⁺ buried islands (subcollector) are examined. By simply modifying layouts of the buried island, the Early voltage (V _A), collector-to-emitter breakdown voltage (BV_CEO), and β×V_A product of transistors are increased from 42, 5.6, and 3070 V to 61, 6.7, and 3820 V, respectively, while the peak cutoff frequency at a V_CE of 1.5 V is decreased from around 21 to 17 GHz. Exploiting these results, it may be feasible to inexpensively integrate transistors with better f _T-BV_CEO and f_T-V_A tradeoffs for analog and power handling characteristics along with transistors optimized for high-speed operation. These results also indicate that the buried island geometry control could be an issue for controlling electrical characteristics for scaled bipolar transistors     

Thickness of diamond-like carbon coatings quantified with Raman spectroscopy

A model is developed for quantifying the thickness of thin coatings and wear scars using Raman spectroscopy. The model, which assumes that both incident and Raman light obey Beer's law, was applied to Raman spectra from a diamond-like carbon (DLC) coating containing Si and O, known as DLN (diamond-like nanocomposite). The coatings ranged in thickness from 10 nm to 2 μm, according to stylus profilometry. Systematic variations in the Raman carbon (G band) and Si (1st order) peak intensities vs. thickness were found. Fits to the model gave an optical mean free path of λ250 nm for DLN. This value is in good agreement with optical absorption coefficient values of other DLC films. Thickness profiles of wear tracks in the coatings determined by the model compared well with depths determined by profilometry.     

Canonical coordinates for transform coding of noisy sources

Based on the additive white quantization noise model, linear transform coders are derived for Gaussian sources corrupted by noise. There are two alternative design objectives: minimizing the trace of the error correlation matrix and thus minimizing the mean-squared error, or minimizing the determinant of the error correlation matrix and thus maximizing information rate. It is shown that a solution to both problems is to first transform the noisy observations into canonical coordinates, quantize and apply a Wiener filter in this coordinate system, and then transform the result back to the original coordinates. Canonical coordinates are uncorrelated, and quantization and Wiener filtering are applied to each component independently. The type of canonical coordinate system depends on the design objective: Quantization in half-canonical coordinates minimizes the mean-squared error and quantization in full-canonical coordinates maximizes information rate. Finally, it is also demonstrated in this paper that majorization is the fundamental principle underlying proofs of optimal transform coding.     

Asymptotic analysis of the MMSE multiuser detector fornonorthogonal multipulse modulation

We develop the minimum mean-squared-error (MMSE) multiuser detector for nonorthogonal multipulse modulation over the noncoherent additive white Gaussian noise channel. We analyze the asymptotic performance of the detector and show that, unlike the case of linear modulation, the MMSE detector does not generally approach the generalized maximum-likelihood (GML) detection rule as the noise power vanishes. It does, however, approach a detector which nulls out the multiaccess interference. This detector is termed the multipulse decorrelating detector due to its similarity to the linear decorrelating detector. The probability of error for this detector is derived and used to find the asymptotic multiuser efficiencies of both the multipulse decorrelating detector and the MMSE detector. It is shown that for noncoherent binary signaling, in which the multipulse modulation is two-dimensional, the multipulse decorrelating detector is superior to the GML detector asymptotically. This result does not generalize to larger dimensionality signal sets