Spectral analysis and discrimination by zero-crossings

Kedem, Benjamin

doi:10.1109/proc.1986.13663

Cited by 250 publications

(128 citation statements)

References 37 publications

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“…The zero-crossing rate (ZCR) is the rate of sign-changes along the signal. In a signal with a single pitched instrument, the ZCR is correlated with the dominant frequency (Kedem, 1986). -Spectral spread, spectral centroid, spectral rolloff Spectral spread and spectral centroid are measures of how power is distributed over frequency.…”

Section: -Fast Fourier Transform Coefficients (Fftcs)mentioning

confidence: 99%

Aggregate features and ADABOOST for music classification

et al. 2006

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We present an algorithm that predicts musical genre and artist from an audio waveform. Our method uses the ensemble learner ADABOOST to select from a set of audio features that have been extracted from segmented audio and then aggregated. Our classifier proved to be the most effective method for genre classification at the recent MIREX 2005 international contests in music information extraction, and the second-best method for recognizing artists. This paper describes our method in detail, from feature extraction to song classification, and presents an evaluation of our method on three genre databases and two artist-recognition databases. Furthermore, we present evidence collected from a variety of popular features and classifiers that the technique of classifying features aggregated over segments of audio is better than classifying either entire songs or individual short-timescale features.

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Section: -Fast Fourier Transform Coefficients (Fftcs)mentioning

confidence: 99%

Aggregate features and ADABOOST for music classification

et al. 2006

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“…Clearly the sign function does not change the number of zero crossings and by using the "The Dominant Frequency Principle" [Ked86] we can uniquely extract the frequency, by counting the number of zero crossings. This property is further explored in figure 2.13 where we give two examples of detecting a frequency even in Gaussian noise and sinusoidal interference.…”

Section: Looking At the Zero Crossingsmentioning

confidence: 99%

UWB waveform generator for digital CMOS radar

Bjorndal

Hamran

Lande³

2015

2015 IEEE International Symposium on Circuits and Systems (ISCAS)

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Small, low cost, radar systems have exciting applications in monitoring and imaging for the industrial, healthcare and Internet of Things (IoT) sectors. We here explore, and show the feasibility of, several single bit square wave radar architectures; that benefits from the continuous improvement in digital technologies for system-on-chip digital integration. By analysis, simulation and measurements we explore novel and harmonic-rich continuous wave (CW), stepped-frequency CW (SFCW) and frequency-modulated CW (FMCW) architectures, where harmonics can not only be suppressed but even utilized for improvements in down-range resolution without increasing on airbandwidth. In addition, due to the flexible digital CMOS implementation, the system is proved by measurement, to feasibly implement pseudo-random noise-sequence and pulsed radars, simply by swapping out the digital baseband processing. Single bit quantization is explored in detail, showing the benefits of simple implementation, the feasibility of continuous time design and only slightly degraded signal quality in noisy environments compared to an idealized analog system. Several iterations of a proof-of-concept 90 nm CMOS chip is developed, achieving a time resolution of 65 ps at nominal 1.2 V supply with a novel Digital-to-Time converter architecture. In pulsed mode, the chip features programmable pulses with a minimum width of 130 ps and a time step of 65 ps. In CW mode, we can transmit arbitrary signals up to 3.8 GHz all the way down to DC. With a continuous time single bit receiver, the backscattered signal can be mixed with the on-chip XOR gate and integrated with the on-chip counters, to provide a system-on-chip CW platform.iii

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“…(i) g (1) is the first-order difference operator. The corresponding finite impulse responses (FIRs) are…”

Section: Filter Bank Implementationmentioning

confidence: 99%

“…Zero crossings or extrema of a signal constitute very important features that have been used in signal processing applications for detection of weak signals, search for periodicity, white-noise testing, and so on, because of their great simplicity [1]. They have also found applications in many engineering fields.…”

Section: Introductionmentioning

confidence: 99%

Fast Frequency Estimation by Zero Crossings of Differential Spline Wavelet Transform

Wang

Chen

et al. 2005

EURASIP J. Adv. Signal Process.

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Zero crossings or extrema of a wavelet transform constitute important signatures for signal analysis with the advantage of great simplicity. In this paper, we introduce a fast frequency-estimation method based on zero-crossing counting in the transform domain of a family of differential spline wavelets. The resolution and order of the vanishing moments of the chosen wavelets have a close relation with the frequency components of a signal. Theoretical results on estimating the highest and the lowest frequency components are derived, which are particularly useful for frequency estimation of harmonic signals. The results are illustrated with the help of several numerical examples. Finally, we discuss the connection of this approach with other frequency estimation methods, with the high-order level-crossing analysis in statistics, and with the scaling theorem in computer vision.

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Spectral analysis and discrimination by zero-crossings

Cited by 250 publications

References 37 publications

Aggregate features and ADABOOST for music classification

Aggregate features and ADABOOST for music classification

UWB waveform generator for digital CMOS radar

Fast Frequency Estimation by Zero Crossings of Differential Spline Wavelet Transform

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