Frequency Subdivision Research Articles

Deep learning algorithm using bispectrum analysis energy feature maps based on ultrasound radiofrequency signals to detect breast cancer.

Ultrasonography is an important imaging method for clinical breast cancer screening. As the original echo signals of ultrasonography, ultrasound radiofrequency (RF) signals provide abundant tissue macroscopic and microscopic information and have important development and utilization value in breast cancer detection. In this study, we proposed a deep learning method based on bispectrum analysis feature maps to process RF signals and realize breast cancer detection. The bispectrum analysis energy feature maps with frequency subdivision were first proposed and applied to breast cancer detection in this study. Our deep learning network was based on a weight sharing network framework for the input of multiple feature maps. A feature map attention module was designed for multiple feature maps input of the network to adaptively learn both feature maps and features that were conducive to classification. We also designed a similarity constraint factor, learning the similarity and difference between feature maps by cosine distance. The experiment results showed that the areas under the receiver operating characteristic curves of our proposed method in the validation set and two independent test sets for benign and malignant breast tumor classification were 0.913, 0.900, and 0.885, respectively. The performance of the model combining four ultrasound bispectrum analysis energy feature maps in breast cancer detection was superior to that of the model using an ultrasound grayscale image and the model using a single bispectrum analysis energy feature map in this study. The combination of deep learning technology and our proposed ultrasound bispectrum analysis energy feature maps effectively realized breast cancer detection and was an efficient method of feature extraction and utilization of ultrasound RF signals.

Downsampling-based synchrosqueezing transform and its applications on large-scale vibration data

Synchrosqueezing transform (SST) is a useful tool for vibration signal analysis due to its high time-frequency concentration and reconstruction properties. However, existing SST requires much processing time and memory for large-scale data. In this paper, some efficient implementation methods of SST based on downsampled short-time Fourier transform are proposed. By controlling the downsampling factor both in time and frequency, combined with the proposed selective reassignment and frequency subdivision scheme, one can keep a balance between efficiency and accuracy according to practical needs. Moreover, the reconstruction property is also available under the downsampling scheme. The effects of parameters on the concentration, computing efficiency, and reconstruction accuracy are also investigated quantitatively, followed by a mathematic model of reassignment behavior affected by decimating factors. Experimental results on an aero-engine and a spindle show that the downsampling-based SST can effectively characterize the non-stationary features of the large-scale vibration data to reveal the mechanism of mechanical systems.

Frequency component vectorisation for image dehazing

ABSTRACT Image captured in bad weather conditions confines scene prominence, appears grey and diminishes image contrast. This usually happens due to atmospheric dispersing phenomenon that affects the quality of outdoor computer vision frameworks. This deprivation relies on the gap between the object point and the camera and mostly differs for every pixel present in an image. Transmission coefficients, which state the aforementioned dependence are used to manage the haze level in each pixel. Our algorithm is subject to the presumption that the haze-free image forms clusters given in RGB space. The pixels over the image plane are often found at different locations and their distance from camera also differs. These fluctuating distances give rise to different transmission coefficients. Consequently, these colour clusters form the certain lines of colours in RGB space known as haze lines. The first step is to assure accurate estimation of the atmospheric light, for this an additional wavelet channel is recommended, based on frequency subdivision. The next step is to separate the average gradients present in the foggy regions of an image according to the frequency criteria. Lastly, the haze-free image information is retrieved by utilising the atmospheric scattering model on low and high frequencies according to the edges of unpredicted change in the field depth. Using the non-local and frequency information retrieval, proposed algorithm recovers the haze-free image, efficiently.

Changes in Dynamics Within and Between Resting-State Subnetworks in Juvenile Myoclonic Epilepsy Occur at Multiple Frequency Bands.

Time-varying connectivity analyses have indicated idiopathic generalized epilepsy (IGE) could cause significant abnormalities in dynamic connective pattern within and between resting-state sub-networks (RSNs). However, previous studies mainly focused on the IGE-induced dynamic changes of functional connectivity (FC) in specific frequency band (0.01–0.08 Hz or 0.01–0.15 Hz), ignoring the changes across different frequency bands. Here, 24 patients with IGE characterized by juvenile myoclonic epilepsy (JME) and 24 matched healthy controls were studied using a data-driven frequency decomposition approach and a sliding window approach. The RSN dynamics, including intra-RSN dynamics and inter-RSN dynamics, was further calculated to investigate dynamic FC changes within and between RSNs in JME patients in each decomposed frequency band. Compared to healthy controls, JME patients not only showed frequency-dependent decrease in intra-RSN dynamics within multiple RSNs but also exhibited fluctuant alterations in inter-RSN dynamics among several RSNs over different frequency bands especially in the ventral/dorsal attention network and the subcortical network. Additionally, the disease severity had significantly negative correlations with both intra-RSN dynamics within the subcortical network and inter-RSN dynamics between the subcortical network and the default network at the lower frequency band (0.0095–0.0195 Hz). These results suggested that abnormal dynamic FC within and between RSNs in JME occurs at multiple frequency bands and the lower frequency band (0.0095–0.0195 Hz) was probably more sensitive to JME-caused dynamic FC abnormalities. The frequency subdivision and selection are potentially helpful for detecting particular changes of dynamic FC in JME.

Signal acquisition technology for photoelectric encoder based on FPGA

This paper studies the method of signal acquisition for the incremental photoelectric encoder based on FPGA. According to the specification of the photoelectric encoder, corresponding interface circuit is designed. With FPGA as the main control module, the peripheral circuit can work together harmoniously. The simulation analysis shows that results of frequency subdivision and direction discrimination are correct under the control of FPGA (Field Programmable Gate Array). A ZSP3806 photoelectric encoder is used as the sensor to detect the position of mirror scanning mechanism, and experimental result indicates that the angular displacement of measured value is consistent with theoretical requirements.

A novel period estimation method for X-ray pulsars based on frequency subdivision

Period estimation of X-ray pulsars plays an important role in X-ray pulsar based navigation (XPNAV). The fast Lomb periodogram is suitable for period estimation of X-ray pulsars, but its performance in terms of frequency resolution is limited by data length and observation time. Longer observation time or oversampling can be employed to improve frequency analysis results, but with greatly increased computational complexity and large amounts of sampling data. This greatly restricts real-time autonomous navigation based on X-ray pulsars. To resolve this issue, a new method based on frequency subdivision and the continuous Lomb periodogram (CLP) is proposed to improve precision of period estimation using short-time observation data. In the proposed method, an initial frequency is first calculated using fast Lomb periodogram. Then frequency subdivision is performed near the initial frequency to obtain frequencies with higher precision. Finally, a refined period is achieved by calculating the CLP in the obtained frequencies. Real data experiments show that when observation time is shorter than 135 s, the proposed method improves period estimation precision by 1–3 orders of magnitude compared with the fast Lomb periodogram and fast Fourier transform (FFT) methods, with only a slight increase in computational complexity. Furthermore, the proposed method performs better than efsearch (a period estimation method of HEAsoft) with lower computational complexity. The proposed method is suitable for estimating periods of X-ray pulsars and obtaining the rotation period of variable stars and other celestial bodies.

Fractal additive synthesis

In this article, we outlined time-frequency techniques that, when brought together, form the basis for FAS. The method is based on an exact orthogonal transform, the HBWT. The FAS model can be seen as an intelligent spectrogram, i.e., as a spectrogram where the frequency bins (the HBWT subbands) are adapted to the spectrum of the analyzed sound by tuning the number of channels P to the period of the sound. Local cosines replace the classical windowed complex exponentials, whose main property is that the basis elements form sidebands of the harmonics rather than being centered on the harmonics themselves. The wavelet transform nonuniform frequency subdivision characteristic is exploited to synthesize each sideband of the harmonic peaks by means of colored noise, generating an approximate pseudoperiodic 1/f behavior. The pseudoharmonics are modeled by narrow sidebands whose weights can be generated by means of amplitude envelopes and phase functions in a complexified HBWT domain. We also showed how perceptual criteria can be employed to reduce the number of synthesis parameters. The possibility of independently controlling the noisy components and the harmonic terms and the definition of parameters such as volumes and envelopes for all of the components independently provide powerful tools for processing voiced-sound for sound design purposes

The Cocktail Party Revisited

The employment of directional information of the desired talker in a multitalker environment has been termed the “cocktail party effect.” We have attempted to determine whether the addition of (1) “comb” filtering, which enhances the perception of spatiality [M. R. Schroeder, J. Acoust. Soc. Am. 29, 774 (1957)], or (2) splitting the speech frequency range, which enhances multichannel listening [W Spieth and J. Webster, J. Acoust. Soc. Am. 27, 866 (1953)] will improve the cocktail party effect, as previously defined [I. Pollack and J. M. Pickett, J. Acoust. Soc. Am. 29, 1262 (1957)]. The introduction of frequency separation does not remove the cocktail party effect. Intelligibility decreases as the frequency subdivision becomes more gross. However, it may be noted that a communication system based upon crude frequency separation and binaural listening may still be effective for certain instances of low-information communications. Specifically, PB monosyllabic word intelligibility of over 30% may be achieved with 4 background talkers in each of two split-frequency channels. This is equivalent to employing 11 transmitters, shared in pairs among 55 different talkers.

Time and Frequency Standards

The quartz clock has made possible a notable improvement in the precision of timekeeping, with the additional advantage of providing a standard of frequency as well. This is perhaps putting the cart before the horse, for the quartz crystal oscillator was developed in the first instance as a precision standard of frequency; it was then adapted, by frequency subdivision and the use of a low frequency output for driving a phonic motor from which seconds impulses could be taken, to serve as a clock. It is primarily from its use as a standard of frequency that it is of navigational interest, for various radio aids to navigation, such as Gee, Loran, Consol and Decca depend upon accurately standardized frequencies. For the satisfactory checking of a frequency, comparison must be made with a standard whose accuracy is at least one degree higher than that of the frequency which has to be checked. Calibration laboratories, in turn, require to check their own standards. As the rotation of the Earth provides our fundamental unit of time, it follows that time, and therefore also frequency, must be determined from astronomical observations; hence it is necessarily the responsibility of the Royal Greenwich Observatory to provide both time and frequency with an accuracy sufficient for all practical requirements. The practical requirements have become more stringent in recent years, and that is why great efforts have been made to improve the precision of time determination and of timekeeping at the Observatory.