Fundamental frequency

About: Fundamental frequency is a research topic. Over the lifetime, 8941 publications have been published within this topic receiving 131583 citations.

Terahertz oscillations in an In0.53Ga0.47As submicron planar Gunn diode

Abstract: The length of the transit region of a Gunn diode determines the natural frequency at which it operates in fundamental mode—the shorter the device, the higher the frequency of operation. The long-held view on Gunn diode design is that for a functioning device the minimum length of the transit region is about 1.5 μm, limiting the devices to fundamental mode operation at frequencies of roughly 60 GHz. Study of these devices by more advanced Monte Carlo techniques that simulate the ballistic transport and electron-phonon interactions that govern device behaviour, offers a new lower bound of 0.5 μm, which is already being approached by the experimental evidence that has shown planar and vertical devices exhibiting Gunn operation at 600 nm and 700 nm, respectively. The paper presents results of the first ever THz submicron planar Gunn diode fabricated in In0.53Ga0.47As on an InP substrate, operating at a fundamental frequency above 300 GHz. Experimentally measured rf power of 28 μW was obtained from a 600 nm long × 120 μm wide device. At this new length, operation in fundamental mode at much higher frequencies becomes possible—the Monte Carlo model used predicts power output at frequencies over 300 GHz.

Interpretations of Frequency Domain Analyses of Neural Entrainment: Periodicity, Fundamental Frequency, and Harmonics

Abstract: Brain activity can follow the rhythms of dynamic sensory stimuli, such as speech and music, a phenomenon called neural entrainment. It has been hypothesized that low-frequency neural entrainment in the neural delta and theta bands provides a potential mechanism to represent and integrate temporal information. Low-frequency neural entrainment is often studied using periodically changing stimuli and is analyzed in the frequency domain using the Fourier analysis. The Fourier analysis decomposes a periodic signal into harmonically related sinusoids. However, it is not intuitive how these harmonically related components are related to the response waveform. Here, we explain the interpretation of response harmonics, with a special focus on very low-frequency neural entrainment near 1 Hz. It is illustrated why neural responses repeating at f Hz do not necessarily generate any neural response at f Hz in the Fourier spectrum. A strong neural response at f Hz indicates that the time scales of the neural response waveform within each cycle match the time scales of the stimulus rhythm. Therefore, neural entrainment at very low frequency implies not only that the neural response repeats at f Hz but also that each period of the neural response is a slow wave matching the time scale of a f Hz sinusoid.

Method and system for controlling combustion engines

Abstract: The invention relates to a method and system for controlling combustion engines by detection of the present air/fuel ratio within the cylinders of the combustion engine, using an analysis of the characteristics of the ionisation current, as detected via a measuring gap with a bias voltage applied being arranged in the combustion chamber, preferably using the spark plug gap in an Otto-engine. A measuring voltage corresponding to the degree of ionisation is detected during the flame ionisation phase and during a time- or crankshaft position dependent period A, B, C or D, which duration is dependent of the present air/fuel ratio, and at finally will be finished by an amplitude maximum PF during the flame ionisation phase. A parameter characteristic for the fundamental frequency of the measuring voltage during the period A, B, C or D is detected, which parameter indicates a tendency towards the rich direction of stochiometric when the fundamental frequency increases, and inversely indicates lean tendency when the fundamental frequency decreases. The fundamental frequency is preferably detected from the differential value of the measuring voltage during the period A, B, C or D, in respect of time t or crankshaft degrees VC, dUION/dt respectively dUION/dVC. The differential value multiplied with a constant is used at least partly when determining a relative or absolute air/fuel ratio.

Analysis of accumulated timing jitter in the time domain

Abstract: This paper deals with the effects of accumulated timing-jitter on the signal-to-noise ratio (SNR) of real sine waves. Such a problem was recently investigated by the author, using the discrete-Fourier method. However, the frequency-domain analysis has some limitations due to the fact that some of the accumulated timing-jitter noise power, found at the fundamental frequency component, would be added to the power of the input signal itself. Thus, in this paper, the analysis is performed in the time-domain and is restricted to the SNR measurement. An expression for the SNR in terms of timing-jitter distribution parameters, and the number of samples of the input signal, is developed. Computer simulations are presented, which showed excellent agreement with the developed expression. Also, a comparison between the results obtained from the time-domain analysis and the frequency-domain, is presented.