The major purpose of this paper is to promote interchange between the fields of pattern recognition and communications, in the realm of statistical classification. The general class of second-order measures of quality...
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The major purpose of this paper is to promote interchange between the fields of pattern recognition and communications, in the realm of statistical classification. The general class of second-order measures of quality for statistical classification is defined. The variety of members in this class that have been used by practitioners or proposed by theorists for numerical pattern-classification and signal waveform-classification are compared and contrasted. The several measures that are the most generally applicable are shown to be either equivalent to each other or characterizable in terms of each other, thereby revealing an inherent unity. For example, the ratio of between-class-scatter to within-class-scatter used in pattern recognition and the ratio of signal-energy to noise-energy used in communications are unified through an identification of signal with between-class-scatter and noise with within-class-scatter. Results on equivalences are stated and proved for waveform classification rather than numerical classification in order to complement the extensive literature on the latter, and to emphasize applicability to communications. This entails introduction of a scatter ratio for waveforms. In a companion paper, second-order measures of quality are used as a basis for a general nearestprototype signal-classification methodology; canonical signal features for this methodology are identified, and a general approach for determining appropriate class prototypes is given. These two papers provide an integrated approach to the design of a complete signal classifier, i.e., feature extraction and discriminant-functional design tailored to fit a minimumdistance discrimination rule.
The use of image quality measures in the design of processing algorithms and equipment is a difficult task. Realistic and useful images are complex and far from the threshold conditions under which psychophysical meas...
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A novel two-stage adaptive signal extractor for intermittent signal applications is presented. If the presence and absence of the signal can be detected, the first stage will adapt only while the signal is absent and ...
A new method of image coding by autoregressive (AR) synthesis is presented. The physics of image formation suggests that an image may be considered as a power spectrum. Using this formulation a Cosine transform of the...
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A new method of image coding by autoregressive (AR) synthesis is presented. The physics of image formation suggests that an image may be considered as a power spectrum. Using this formulation a Cosine transform of the sampled image is shown to yield a set of autocorrelations. These are used to find an equivalent AR model whose parameters are encoded for transmission. Compared to conventional Cosine transform coding, this method is shown to give superior resolution and is shown to suppress the "block-effects" present in block-by-block transform coding methods. Distinction between this method and linear predictive coding (LPC) used for speech data compression is made. Extensions and examples for two dimensional images are given.
With their high relative permeability and high permittivity, magneto-dielectric materials show great potential in tunable bandpass filter designs. This paper presents a novel tunable bandpass filter with magneto-diele...
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