Abstract: An enhanced tone detector including an adaptive multi-bandpass filter, a tone detector and a filter control unit. The adaptive multi-bandpass filter has a signal input receiving an input signal, a signal output providing a filtered signal, and at least one control input for receiving at least one control signal. The tone detector has an input coupled to the signal output of the adaptive multi-bandpass filter and at least one output providing at least one tone detection signal when a tone event is detected. The filter control unit has a first input receiving the input signal, at least one second input receiving the at least one tone detection signal, and at least one first output providing the at least one control signal. The control signals may include one or more frequency component signals and corresponding bandwidth signals in which the frequency component signals correspond to component frequencies of a tone event.

Abstract: Methods and corresponding systems for suppressing noise in an input signal include setting a minimum overall gain in a noise reduction processor for processing a first frame of data associated with the input signal. In response to a new minimum overall gain being set, the minimum overall gain in the noise reduction processor is replaced with the new minimum overall gain, and a second frame of data associated with the input signal is processed to suppress noise using the new minimum overall gain. The new minimum overall gain can be a function of the input signal or an output signal of the noise reduction processor. The new minimum overall gain can correspond to a difference between an estimated signal-to-noise ratio (SNR) improvement that is calculated using time-domain data and a target SNR improvement.

Abstract: Methods and corresponding systems for allocating processing resources for a number of instances (N) of a software component include determining an average processing cost (?) and a variance (?2) for the software component. Then a processing cost for the software component is estimated as a function of N, the average processing cost (?), and the variance (?2), and processing resources are allocated in response to the estimated processing cost. The software component can be partitioned into a number of blocks (L), wherein the L blocks include a required block and one or more optional blocks. In some embodiments in response to a total estimated processing cost exceeding an available processing value, selected optional blocks can be disabled to reduce the total estimated processing cost to a value equal to or less than the available processing value. The optional blocks can be prioritized and disabled in order of priority.

Abstract: A system (301) and corresponding method (1200) are arranged for detecting reflections in a communication channel. The system comprises first and second multi-rate filters (311, 313) having bandpass characteristics and configured to provide first and second filtered signals, a sub rate adaptive filter (315) configured to process the filtered signals to provide filter coefficients; and a coefficient analyzer (317) configured to analyze the filter coefficients and provide a time delay corresponding to each of one or more reflections.

Abstract: A method, computer program product, and data processing system for performing automated optimization of a control processing flow containing Boolean conditional expressions is disclosed. Each conditional expression is profiled using a representative set of test vectors to determine the probabilities of individual conditions and combinations of conditions in the expression. Next, the expression is restructured or reordered, including selective computation of subexpressions, based on the probability information, so as to maximize the probability of a short-circuit termination of evaluation of the expression and/or to minimize the statistical execution time of the expression. This process is performed for all Boolean conditional expressions related to the control processing flow.

Abstract: A method and apparatus are provided for mixing a plurality of signals within a predetermined dynamic range without clipping. In the method and apparatus, first and second signal samples are added together to obtain a first intermediate result. Then the first signal sample is multiplied with the second signal sample to obtain a second intermediate result. In one embodiment, the second intermediate result is subtracted from the first intermediate result to obtain a third intermediate result, and the third intermediate result is discarded if the third intermediate result is less than zero. In another embodiment, the second intermediate result is added to the first intermediate result to obtain the third intermediate result, and the third intermediate result is discarded if the third intermediate result is greater than zero. An output signal sample is provided based on the third intermediate result.

Abstract: In one embodiment, a tone event detector first determines whether the presence of a tone is indicated on the input signal, and then, based on this determination, selectively determines whether a tone has been detected on the input signal. For example, in one embodiment, tone detection is performed only when the presence of a tone is first indicated, such that if the presence of a tone is not indicated, tone detection need not be performed. This may help reduce complexity of a tone event detector since a simplified method may be used to indicate the presence of a tone, and the more complex algorithms for tone detection may be enabled only when needed. Also, in one embodiment, detection of a tone includes generating one or more tone characteristics corresponding to the detected tone which may then be used to determine whether the detected tone corresponds to a valid tone event.

Abstract: A method and apparatus for dynamically inserting gain in an adaptive filter is taught. This selective insertion of gain may be used to allow an adaptive filter to converge more quickly and/or to overcome inherent limitations of the adaptive filter. An echo canceller (e.g. 20 and 22 in FIG. 1) is just one possible use for an adaptive filter having a shorter convergence time. However, virtually all uses of an adaptive filter can benefit from a shorter convergence time and/or improved filtering performance.

Abstract: A method for fast training of equalizers in a DMT system begins by normalizing the incoming receive signal (&ngr;) via steps (108-116). By normalizing the signal, the convergence rate of the training algorithm becomes relatively independent of channel line length so that long line lengths may converge to optimal equalizer coefficients in short time periods. The method also iteratively adjusts the filter coefficients w over time by using an adaptive gain vector &mgr; that is updated on a component-by-component basis on each iteration via steps (114-146). By allowing each component of the vector &mgr; to iteratively adapt independent of all other components in the vector &mgr; based upon the binary sign bit of both real and imaginary components of frequency domain gradient vectors G, a convergence to optimal equalizer filter coefficients will occur in a short period of time.