An all-pole modeling technique, Linear Prediction with Lowfrequency Emphasis (LPLE), which emphasizes the lower frequency range of speech, is presented. The method is based on first interpreting conventional linear predictive (LP) analyses of successive prediction orders with parallel structures using the concept of symmetric linear prediction. In these implementations, symmetric linear predict...

Abstract. The refinement equation φ(t) = ∑N2 k=N1 ck φ(2t − k) plays a key role in wavelet theory and in subdivision schemes in approximation theory. Viewed as an expression of linear dependence among the time-scale translates |a|1/2φ(at − b) of φ ∈ L2(R), it is natural to ask if there exist similar dependencies among the time-frequency translates e2πibtf(t + a) of f ∈ L2(R). In other words, wh...

—The simplest diploid model of frequency-dependent selection can generate periodic and chaotic trajectories for the allele frequency. The model is of a randomly mating, infinite diploid population with non-overlapping generations, segregating for two alleles under frequency-dependent viability selection. The fitnesses of each of the three genotypes is a linear function of the frequencies of the...

Linear probing of a scatte r (or hash) table interpre ts each key or item (these terms are inte rchangea ble here) as a probe index into the table [1]. 1 Typically, a key is divided by the table size and the remainder is used for indexing. If the selected slot is empty, the item is not present. Should the slot contain some other key, eacl1 next highe r location is checked until the item is foun...

We present an efficient method for robustly calculating time–frequency attributes of a signal, including instantaneous mean frequency, bandwidth, kurtosis, and other moments. Most current attribute estimation techniques involve a costly intermediate step of computing a (highly oversampled) two-dimensonal (2-D) quadratic time–frequency representation (TFR), which is then collapsed to the one-dim...

The maximum-likelihood estimation of the parameters of linear systems and the properties of the estimator (Estimator for Linear Systems, ELiS) have been described in a paper by R. Pintelon and J. Schoukens (“Robust identification of transfer functions in sand z-domain,” IEEE TRANSACTIONS Aug. 1990). The mathematics used in the development of the method and the proofs are rather involved. Howeve...

We consider linear discriminant analysis in the setting where the objects signals images have many dimensions samples pixels and there are relatively few training samples We discuss ways that time frequency dictionaries can be used to adaptively select a small set of derived features which lead to improved misclassi cation rates

The paper presents a novel linear, high-fidelity millimetre displacement-to-frequency transducer, based on the resistive conversion of displacement into a proportional voltage, and then frequency. The derivation of the nonlinearity, fidelity and sensitivity of the transducer is presented. Experimental results confirm that a displacement of 0-100 mm is converted into a frequency range of 0-100 k...

Current speech recognition systems uniformly employ short-time spectral analysis, usually over windows of 1030 ms, as the basis for their acoustic representations. Any detail below this timescale is lost, and even temporal structure above this level is usually only weakly represented in the form of deltas etc. We address this limitation by proposing a novel representation of the temporal envelo...

Extending previous works done on considerably smaller data sets, the paper studies linear discriminant analysis of about 30 hours of phoneme-labeled speech data in the time-frequency domain. Analysis is carried both independently in time and frequency and jointly. Data driven spectral basis show similar frequency sensitivity as human hearing. LDA-derived temporal FIR filters are consistent with...