Abstract: A method (20) of orthogonal frequency-division multiplex (OFDM) communication via a plurality of subchannels (30) within a noncontiguous wideband channel (24) is provided. The method (20) determines an SNR for each of the subchannels (30). The method (20) then designates a subchannel (30) as clear (93) when its SNR is greater than a least-SNR threshold (70), as impeded (95) when its SNR is less than the least-SNR threshold and greater than an SNR-evaluation threshold, and as obstructed (111) when its SNR is less than both the least-SNR and the SNR-evaluation thresholds. The method (20) then transmits OFDM data (34) so that each of the clear subchannels receives the OFDM data (34) at a maximum subchannel signal level (40), each of the impeded subchannels receives the OFDM data (34) at an intermediate subchannel signal level (42), and each of the obstructed subchannels receives the OFDM data (34) at zero subchannel signal level (44).

Abstract: Apparatus are provided for a communication signal processing apparatus having a channel estimator configured to generate a first channel estimation at a first time point, a linear predictor coupled to the channel estimator, and an adaptive filter coupled with the linear predictor. The linear predictor is configured to predict a second channel estimation based on a second time point and a channel frequency. The second time point is concurrent or subsequent to the first time point. The second channel estimation includes a first coefficient. The linear predictor includes a first predictor having a sample time point. The first predictor is configured to generate the first coefficient of the second channel estimation based on the sample time point and the second time point. The sample time point is prior to the second time point. The adaptive filter is configured to recursively determine the second channel estimation.

Abstract: A symbol synchronizer (100) is provided for a software-defined communications system (10). The symbol synchronizer (100), when integrated into either a pre- or post-detection diversity signal combiner (108, 208), enables highly accurate signal synchronization with minimal added system complexity. The symbol synchronizer (100) includes a single complex sliding window-matched filter (102) for filtering an input digital signal with a match filtering function based on predetermined signal transfer function characteristics to average out receiver noise from the signal. A signal delay bank (84) includes a plurality of delay blocks each for delaying the digital signal filtered by the single matched filter for a predetermined number of samples. A complex correlator (88) correlates the digital signal filtered by the single complex sliding window matched filter (102) and delayed by the complex correlator (88) with a correlator reference signal, and selects an index of a path having a peak correlator value.

Abstract: A symbol synchronizer (100) is provided for a software-defined communications system (10). The symbol synchronizer (100), when integrated into either a pre- or post-detection diversity signal combiner (108, 208), enables highly accurate signal synchronization with minimal added system complexity. The symbol synchronizer (100) includes a single complex sliding window matched filter (102) for filtering an input digital signal with a match filtering function based on predetermined signal transfer function characteristics to average out receiver noise from the signal. A signal delay bank (84) includes a plurality of delay blocks each for delaying the digital signal filtered by the single matched filter for a predetermined number of samples. A complex correlator (88) correlates the digital signal filtered by the single complex sliding window matched filter (102) and delayed by the complex correlator (88) with a correlator reference signal, and selects an index of a path having a peak correlator value.

Abstract: An improved method of training a SISRS uses less processing and memory resources by operating on vectors instead of matrices which represent spoken commands. Memory requirements are linearly proportional to the number of spoken commands for storing each command model. A spoken command is identified from the set of spoken commands by a command recognition procedure (200). The command recognition procedure (200) includes sampling the speaker's speech, deriving cepstral coefficients and delta-cepstral coefficients, and performing a polynomial expansion on cepstral coefficients. The identified spoken command is selected using the dot product of the command model data and the average command structure representing the unidentified spoken command.

Abstract: A method and apparatus (100) for pitch-epoch-synchronous source-filter speech encoding by means of error component modeling methods (310) which capture fundamental orthogonal (uncorrelated) basis elements of an excitation source waveform. A periodic waveform model (318) along with four orthogonal error waveforms, desirably including phase error (319), ensemble error (321), standard deviation error (323), and mean error (324) waveforms, are incorporated together to form a complete description of the excitation. These error waveforms (319,321, 323, 324) represent those portions of the excitation that are not represented by the purely periodic model. By thus orthogonalizing the error components, the perceptual effect of each element is isolated from the composite set, and can thus be encoded separately.

Abstract: A speech coder (100) computes scalar statistics (180), ensemble statistics (190), spectral parameters (150), and a normalized excitation waveform (270) which describe a frame of speech samples. The coder (100) encodes the statistics (220, 230), spectral parameters (155), and the normalized waveform (290) for later decoding and synthesis. A speech synthesizer (900) decodes the encoded scalar statistics (570), encoded ensemble statistics (560), encoded spectral parameters (490), and encoded normalized excitation waveform (550). The synthesizer (900) then denormalizes (670) the normalized excitation waveform using the scalar statistics and the ensemble statistics, resulting in a decoded excitation waveform. Speech is synthesized (710) from the decoded excitation waveform and the decoded spectral parameters.