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Techniques studied involve conversion of speech sounds into machine-compatible pulse trains. (1) Voltage-level quantizer produces number of output pulses proportional to amplitude characteristics of vowel-type phoneme waveforms. (2) Pulses produced by quantizer of first speech formants are compared with pulses produced by second formants.
Dynamic modeling of a low cost single axis LST system and the pointing stability of that system are investigated. The effects of nonlinear friction of the bearings of the reaction wheels, quantization, and sensor noise on the pointing error are covered. In addition, data are given on self sustained oscillations of the system induced by quantization and methods of evaluating attitude error of the digital LST.
A mathematical model employing Fourier series is used to show quantization and reaction wheel friction nonlinearity in a telescope system for use in space. Block diagrams are used to illustrate the system. A discrete describing function of a quantizer also is given, and input and output signal waveforms, with illustrative examples, are shown.
An expression for the information capacity of the optical-mechanical line-scan imaging process is derived which includes the effects of blurring of spatial, photosensor noise, aliasing, and quantization. Both the information capacity for a fixed data density and the information efficiency (the ratio of information capacity to data density) exhibit a distinct single maximum when displayed as a function of sampling rate, and the location of this maximum was determined by the system frequency-response shape, signal-to-noise ratio, and quantization interval.
Computer simulation of data transmission over a noncoherent channel with predetection signal-to-noise ratio of 1 shows that convolutional coding can reduce the energy requirement by 4.5 dB at a bit error rate of 0.001. The effects of receiver quantization and choice of number of tones are analyzed; nearly optimum performance is attained with eight quantization levels and sixteen tones at predetection S/N ratio of 1. The effects of changing predetection S/N ratio are also analyzed; for lower predetection S/N ratio, accurate extrapolations can be made from the data, but for higher values, the results are more complicated. These analyses will be useful in designing telemetry systems when coherence is limited by turbulence in the signal propagation medium or oscillator instability.
Optical-mechanical line-scan techniques have been applied to earth satellite multispectral imaging systems. The capability of the imaging system is generally assessed by its information capacity. An approach based on information theory is developed to formulate the capacity of the line-scan process. Included are the effects of blurring of spatial detail, photosensor noise, aliasing, and quantization. The information efficiency is shown to be dependent on sampling rate, system frequency response shape, SNR, and quantization interval.
The quantum principles that establish the energy levels and degeneracies needed to evaluate the partition functions are explored. The uncertainty principle is associated with the dual wave-particle nature of the model used to describe quantized gas particles. The Schroedinger wave equation is presented as a generalization of Maxwell's wave equation; the former applies to all particles while the Maxwell equation applies to the special case of photon particles. The size of the quantum cell in phase space and the representation of momentum as a space derivative operator follow from the uncertainty principle. A consequence of this is that steady-state problems that are space-time dependent for the classical model become only space dependent for the quantum model and are often easier to solve. The partition function is derived for quantized free particles and, at normal conditions, the result is the same as that given by the classical phase integral. The quantum corrections that occur at very low temperatures or high densities are derived. These corrections for the Einstein-Bose gas qualitatively describe the condensation effects that occur in liquid helium, but are unimportant for most practical purposes otherwise. However, the corrections for the Fermi-Dirac gas are important because they quantitatively describe the behavior of high-density conduction electron gases in metals and explain the zero point energy and low specific heat exhibited in this case.
The performance of convolutional codes in conjunction with noncoherent multiple frequency shift-keyed (MFSK) modulation and Viterbi maximum likelihood decoding on a Rician fading channel is examined in detail. While the primary motivation underlying this work has been concerned with system performance on the planetary entry channel, it is expected that the results are of considerably wider interest. Particular attention is given to modeling the channel in terms of a few meaningful parameters which can be correlated closely with the results of theoretical propagation studies. Fairly general upper bounds on bit error probability performance in the presence of fading are derived and compared with simulation results using both unquantized and quantized receiver outputs. The effects of receiver quantization and channel memory are investigated and it is concluded that the coded noncoherent MFSK system offers an attractive alternative to coherent BPSK in providing reliable low data rate communications in fading channels typical of planetary entry missions.
The general problem of image data compression is discussed briefly with attention given to the use of Karhunen-Loeve transforms, suboptimal systems, and block quantization. A survey is then conducted encompassing the four categories of adaptive systems: (1) adaptive transform coding (adaptive sampling, adaptive quantization, etc.), (2) adaptive predictive coding (adaptive delta modulation, adaptive DPCM encoding, etc.), (3) adaptive cluster coding (blob algorithms and the multispectral cluster coding technique), and (4) adaptive entropy coding.
'Second-order quantizers' are introduced which can be used for implementing recursive digital filters with practically no roundoff errors or limit-cycle oscillations. Based on the idea of changing the transfer function used to compute roundoff errors, these quantizers save the low-order bits to correct the product at future iterations. For several pole locations, this can be done with a minimal amount of extra hardware.
Techniques developed for the finite-precision implementation of digital filters were used, adapted, and extended for digital feedback compensators, with particular emphasis on steady state, linear-quadratic-Gaussian compensators. Topics covered include: (1) the linear-quadratic-Gaussian problem; (2) compensator structures; (3) architectural issues: serialism, parallelism, and pipelining; (4) finite wordlength effects: quantization noise, quantizing the coefficients, and limit cycles; and (5) the optimization of structures.
A block adaptive rate controlled (BARC) image data compression algorithm is described. It is noted that in the algorithm's principal rate controlled mode, image lines can be coded at selected rates by combining practical universal noiseless coding techniques with block adaptive adjustments in linear quantization. Compression of any source data at chosen rates of 3.0 bits/sample and above can be expected to yield visual image quality with imperceptible degradation. Exact reconstruction will be obtained if the one-dimensional difference entropy is below the selected compression rate. It is noted that the compressor can also be operated as a floating rate noiseless coder by simply not altering the input data quantization. Here, the universal noiseless coder ensures that the code rate is always close to the entropy. Application of BARC image data compression to the Galileo orbiter mission of Jupiter is considered.
Three kinds of artifacts unique to digital images are illustrated, namely aliasing caused by undersampling, interference phenomena caused by improper display of images, and harmonic overtones caused by quantization of amplitudes. Special attention is given to undersampling when the sample size and interval are the same. It is noted that this situation is important because it is typical of solid-state cameras. Quantization of image data of necessity introduces energy at harmonic overtones of the image spectrum. This energy is aliased if the frequency of the overtones is greater than 0.5 cycle/pixel. It cannot be selectively removed from the image through filtering, and the best way to suppress it is to maximize the amplification of the sensor before digital encoding.
A simple monochrome conditional replenishment system was extended to higher compression and to higher motion levels, by incorporating spatially adaptive quantizers and field repeating. Conditional replenishment combines intraframe and interframe compression, and both areas are investigated. The gain of conditional replenishment depends on the fraction of the image changing, since only changed parts of the image need to be transmitted. If the transmission rate is set so that only one fourth of the image can be transmitted in each field, greater change fractions will overload the system. A computer simulation was prepared which incorporated (1) field repeat of changes, (2) a variable change threshold, (3) frame repeat for high change, and (4) two mode, variable rate Hadamard intraframe quantizers. The field repeat gives 2:1 compression in moving areas without noticeable degradation. Variable change threshold allows some flexibility in dealing with varying change rates, but the threshold variation must be limited for acceptable performance.
Information density and efficiency (i.e., the ratio of information density to data density) are used as criteria for assessing the quality of 2-D sampled and quantized imagery as a function of the statistical properties of random radiance fields, the spatial response (PSF or MTF) and sensitivity of imaging systems, and the sampling and quantization intervals. Computational results are intuitively satisfying: they are consistent with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV cameras, and they provide useful guidelines for optimizing the design of line-scan and sensor-array imaging systems, especially if these systems use a digital communication link for transmitting data.
The feasibility of designing a digital, complex, baseband mixer with a 50 MHz sampling rate is explored. The baseband filter must provide passbands with linear phase response to minimize intersymbol interference. The effects of signal quantization, filter coefficient quantization, dynamic range, filter response characteristics, and the performance of the mixer when used for cross correlation and autocorrelation pulse detection techniques are discussed. This filter was designed for use in the high speed data acquisition system (HSDAS), an advanced experimental system in the Deep Space Network.
Permutation codes for the Laplacian source are developed. The performance of these codes is evaluated and compared with other quantizers and the rate-distortion function. It is shown that there is a bit-rate region in which the permutation codes outperform certain single-sample quantizers.
Selected sensor parameter differences between TM and MSS were assessed through classification performance of a suburban/regional test site. Overall classification accuracy of a seven-band Landsat TM scene in comparison to MSS yielded an improvement in accuracy from 74.8 percent to 83.2 percent. To study the possible causes for the difference in classification performance, key sensor parameter differences between MSS and TM, including: (1) spatial resolution (30 m for TM versus 80 m for MSS), (2) quantization level (256 levels for TM versus 64 for MSS), and (3) spectral regions (seven bands in four major spectral regions for TM versus four bands in two regions for MSS), were evaluated. Landsat TM data were processed to stimulate all possible combinations of these MSS and TM parameters, yielding a three-factor design with two levels per factor. The results indicated that the added spectral regions (TM 1, TM 5, and TM 7) and to a lesser degree the increase in quantization level to eight bits produced the improved TM classification accuracy. However, in this study, the higher 30 m spatial resolution of TM contributed to a reduced classification accuracy from increased within-field variability or class heterogeneity.