Audio filter

Abstract: The electromagnetic (EM) spectrum is becoming more crowded, and it is densely populated with various wireless signals and parasitic interferers in connection with communication and sensing services. Increasingly sophisticated radio-frequency (RF), microwave, and millimeter-wave filters are required to enable the selection and/or rejection of specific frequency channels. This will occur in future generations of the wireless system, such as the current hotly debated fifth-generation communication systems, where the spectral channelization of a heterostructured wide-band signals will be critical in support of a host of coexisting bandwidths or speeds and applications. Bandpass filters have been the most useful and popular types for such applications and are the most difficult to design and develop in practice. Other types of filters such as notch (stopband) and lowpass filters have also been widely used in many systems, and their design is generally perceived less critical with respect to band-pass filters. This article will focus on the presentation and discussion of bandpass filters. Design factors or parameters of filters, such as selectivity, cost, miniaturization, sensitivity to environmental effects (temperature and humidity, for example), and power handling, combined with predefined in-band and out-of-band performance metrics, are critical specifications of the design with respect to the development of RF and microwave front ends. This is indispensable for the efficient utilization of frequency spectrum resources and the cost-effective enhancement of wireless system performances.

Abstract: Estimating the proximity of an audio source (14, 15) is accomplished by transforming audio signals from a plurality of sensors (18, 20) to frequency domain. The amplitudes of the transformed audio signals are then determined. The proximity of the audio source is determined based on a comparison of the frequency domain amplitudes. This estimation permits a device (16) to differentiate between relatively distant audio sources (14) and audio sources (15) at close proximity to the device. The technique can be applied to mobile handsets, such as cellular phones or PDAs, hands-free headsets, and other audio input devices. Devices taking advantage of this "close proximity" detection are better able to suppress background noise and deliver an improved user experience.

Abstract: A subband audio coder employs perfect/non-perfect reconstruction filters, predictive/non-predictive subband encoding, transient analysis, and psycho-acoustic/minimum mean-square-error (mmse) bit allocation over time, frequency and the multiple audio channels to encode/decode a data stream to generate high fidelity reconstructed audio. The audio coder windows the multi-channel audio signal such that the frame size, i.e. number of bytes, is constrained to lie in a desired range, and formats the encoded data so that the individual subframes can be played back as they are received thereby reducing latency. Furthermore, the audio coder processes the baseband portion (0-24 kHz) of the audio bandwidth for sampling frequencies of 48 kHz and higher with the same encoding/decoding algorithm so that audio coder architecture is future compatible.

Abstract: A method and a control circuit for controlling an output of an audio signal of a battery-powered device are described. The charge condition of the battery is determined and in case of low charge level, the audio filter/gain parameter and/or the audio compression parameter are adjusted to reduce power consumption, thus allowing longer reproducing time by lower sound quality.