Abstract: A method and apparatus determine parameters and conditions for line of sight MIMO communication. A transmitter can transmit reference symbols from a regularly spaced subset of a set of transmitting device antenna elements of the transmitter with elements spanning one or more spatial dimensions. The transmitter can signal transmit antenna element spacings in each dimension that can be used by the transmitter for data transmission.

Abstract: A method and apparatus determine parameters and conditions for line of sight MIMO communication. Reference signals can be received at a receiving device from a transmitting device. A channel matrix can be measured based on the reference signals. At least two of a first line of sight channel parameter, a second line of sight channel parameter, and a third line of sight channel parameter can be extracted based on the channel matrix. The first line of sight channel parameter can be based on transmitting device antenna element spacing. The second line of sight channel parameter can be based on a product of the transmitting device antenna element spacing and a receiving device antenna element spacing. The third line of sight channel parameter can be based on the receiving device antenna element spacing. The at least two line of sight channel parameters can be transmitted to the transmitting device.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: A digital information encoder including a divider configured to divide a block of information into a plurality of sub-parts, an initial bit allocator configured to perform an initial allocation of bits to a KTH sub-part of said plurality of sub-parts, a processor configured to compute an estimated number of bits for encoding said KTH sub-part, and a bit allocation adjuster configured to obtain an adjusted bit allocation for said KTH sub-part by adjusting said initial allocation of bits to said KTH sub-part based, at least in part, on said estimated number of bits, wherein the encoder encodes said KTH sub-part using said adjusted bit allocation for said KTH sub-part.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Disclosed are systems and methods for the efficient conversion of linear predictive coefficients. This method is usable, for example, in the conversion of full band linear predictive coding (“LPC”) coefficients to sub-band LPCs of a sub-band speech codec. The sub-bands may or may not be down-sampled. In an embodiment, the LPC coefficients of the sub-bands are obtained from the correlation coefficients, which are in turn obtained by filtering the auto-regressive extended auto-correlation coefficients of the full band LPCs. The method also allows the generation of an LPC approximation of a pole-zero weighted synthesis filter.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: Improved methods for coding an ensemble of pulse vectors utilize statistical models (i.e., probability models) for the ensemble of pulse vectors, to more efficiently code each pulse vector of the ensemble. At least one pulse parameter describing the non-zero pulses of a given pulse vector is coded using the statistical models and the number of non-zero pulse positions for the given pulse vector. In some embodiments, the number of non-zero pulse positions are coded using range coding. The total number of unit magnitude pulses may be coded using conditional (state driven) bitwise arithmetic coding. The non-zero pulse position locations may be coded using adaptive arithmetic coding. The non-zero pulse position magnitudes may be coded using probability-based combinatorial coding, and the corresponding sign information may be coded using bitwise arithmetic coding. Such methods are well suited to coding non-independent-identically-distributed signals, such as coding video information.

Abstract: A method (1100) and apparatus (100) generate a candidate code-vector to code an information signal. The method can include producing (1110) a weighted target vector from an input signal. The method can include processing (1120) the weighted target vector through an inverse weighting function to create a residual domain target vector. The method can include performing (1130) a first search process on the residual domain target vector to obtain an initial fixed codebook code-vector. The method can include performing (1140) a second search process over a subset of possible codebook code-vectors for a low weighted-domain error to produce a final fixed codebook code-vector. The subset of possible codebook code-vectors can be based on the initial fixed codebook code-vector. The method can include generating (1150) a codeword representative of the final fixed codebook code-vector. The codeword can be for use by a decoder to generate an approximation of the input signal.

Abstract: The invention utilizes low complexity estimates of complex functions to perform combinatorial coding of signal vectors. The invention disregards the accuracy of such functions as long as certain sufficient properties are maintained. The invention in turn may reduce computational complexity of certain coding and decoding operations by two orders of magnitude or more for a given signal vector input.

Abstract: A method and apparatus provides for frame loss recovery following a loss of a frame in an audio codec. The lost frame is identified. Estimated linear predictive coefficients of a previous transform frame are generated based on a decoded audio of the previous transform frame. An estimated residual of the previous transform frame is generated based on the estimated linear predicative coefficients and the decoded audio. A pitch delay is determined from frame error recovery parameters received with the previous transform frame. An extended residual is generated based on the pitch delay and the estimated residual. A first synthesized signal is generated based on the extended residual and the linear predicative coefficients. A decoded audio output of at least the lost frame is generated based on the first synthesized signal. The frame error recovery parameters are generated by an encoder.

Abstract: A method (300) and apparatus (100) generate a candidate code-vector to code an information signal. The method can include producing (310) a target vector from a received input signal. The method can include constructing (320) a plurality of inverse weighting functions based on the target vector. The method can include evaluating (330) an error value associated with each of the plurality of inverse weighting functions to produce a fixed codebook code-vector. The method can include generating (340) a codeword representative of the fixed codebook code-vector, where the codeword can be used by a decoder to generate an approximation of the input signal.

Abstract: In a speech encoder/decoder a pitch delay contour endpoint modifier is employed to shift the endpoints of a pitch delay interpolation curve up or down. Particularly, the endpoints of the pitch delay interpolation curve are shifted based on a variation and/or a standard deviation in pitch delay.

Abstract: A method and apparatus provide for audio frame recovery by identifying a sequence of lost frames of coded audio data as being lost or corrupted; identifying a first frame of coded audio data which immediately preceded the sequence of lost frames, as having been encoded using a time domain coding method; identifying a second frame of coded audio data, which immediately followed the sequence of lost frames of coded audio data, as having been encoded using a transform domain coding method; obtaining a pitch delay; generating a second decoded audio portion of the second frame based on the second frame; generating a first decoded audio portion of the second frame based on the pitch delay and decoded audio samples; and generating a decoded audio output of the second frame based on a sequential combination of the first and second decoded audio portions.