A digital filter circuit is described. The digital filter circuit includes a digital filter input, at least two finite impulse response (FIR) filter circuits, and a connection circuit. The digital filter input is configured to receive a digital input signal set having a data parallelism. The at least two FIR filter circuits are configured to process the digital input signal set at least partially. The at least two FIR filter circuits include a pre-adder sub-circuit, a convolution sub-circuit, and a post-adder sub-circuit, respectively. The connection circuit is configured to selectively connect the at least two FIR filter circuits based on the data parallelism of the digital input signal set.

Method for monitoring a stable convergence behaviour of a Kalman filter (KF), which estimates states and/or parameters of an energy storage system, in particular a battery cell (BZ), wherein a covariance behaviour—provided by the Kalman filter (KF)—in terms of at least one state and/or parameter of the energy storage system is compared with a corresponding desired covariance behaviour of the state and/or parameter, wherein the Kalman filter (KF) is automatically deactivated for each state and/or each parameter of the energy storage system, of which the covariance behaviour exceeds the corresponding desired covariance behaviour.

Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

An oversampling channelizer for processing overlapping data that includes a data storage unit, coupled to a data line that receives data values. The data storage unit includes a plurality of lanes, wherein each of the plurality of lanes includes dedicated memory locations and wires that store and transmit data values for a data vector of a data frame, and that store and transmit additional data values for a subsequent data vector of a subsequent data frame that includes a plurality of the data values from the data vector in the data frame. The oversampling channelizer includes a coefficient storage unit that stores a plurality of coefficient vectors for a plurality of coefficient frames. The oversampling channelizer includes a computation unit that computes a dot product of the data values for the data vectors of the data frame with coefficient values for coefficient vectors of a coefficient frame selected by a coefficient storage unit.

A polyphase decimation FIR filter apparatus including a modulo integrator circuit configured to integrate input samples and to provide integrated input samples; and a polyphase FIR filter circuit configured to process the integrated input samples, the polyphase FIR filter circuit including a plurality of multiplier accumulator circuits, each configured to accumulate products of coefficients and respective integrated signal samples, wherein each of the multiplier accumulator circuits receives a subset of FIR filter coefficients, wherein the FIR filter coefficients are derived as the nth difference of original filter coefficients, where n is a number of integrators in the integrator circuit, and wherein the FIR filter circuit is configured to perform computation operations with modulo arithmetic.

A common sub-expression elimination method for simplifying hardware logic of a hardware filter circuit by eliminating a common sub-expression included in a plurality of sub-expressions is provided. Each of the sub-expressions includes a corresponding two or more of inputs constituting a plurality of coefficients used by the hardware filter circuit. The method is implemented on a computing device and includes: identifying for each coefficient of the plurality of coefficients, a combination of the inputs constituting the coefficient; counting occurrences of the sub-expressions in each of the coefficients; identifying one or more of the sub-expressions having a maximum one of the counts and including the corresponding two or more of the inputs; selecting one of the one or more of the sub-expressions as the common sub-expression; eliminating the common sub-expression; and repeating these steps to eliminate more of the sub-expressions common to multiple ones of the coefficients.

A microprocessor system comprises a computational array and a hardware data formatter. The computational array includes a plurality of computation units that each operates on a corresponding value addressed from memory. The values operated by the computation units are synchronously provided together to the computational array as a group of values to be processed in parallel. The hardware data formatter is configured to gather the group of values, wherein the group of values includes a first subset of values located consecutively in memory and a second subset of values located consecutively in memory. The first subset of values is not required to be located consecutively in the memory from the second subset of values.

A method of increasing the sample rate of a digital signal by creating intermediate sample points between adjacent neighbouring sample points comprising the step of populating each of the intermediate sample points depending on a weighted influence of a predetermined number of the neighbouring sample points, the weighted influence being calculated by representing the digital signal or filter at the predetermined number of sample points at least in part by its cosine components, which are each represented by absolute values of a cosine function in the time domain substantially limited to half a waveform cycle at its mid-point; combining the aforementioned cosine components at each of the neighbouring sample points to obtain waveforms at each of the neighboring sample points; determining values for each of the waveforms at the intermediate sample points and combining the determined values at the intermediate sample point to derive the weighted influence.

A method of processing a digital signal includes providing a digital filter including neighbouring sample points and performing a sample rate increase on the digital filter to provide intermediate sample points between adjacent neighbouring sample points, said intermediate points being populated dependent on a weighted influence determined in the time domain of a predetermined number of the neighbouring sample points. The digital filter is applied to the signal where: i) one of the neighbouring sample points of the filter is applied to a corresponding sample point of the signal; ii) offset and neighbouring sample points of the signal are defined either side of the corresponding sample point, said offset points being offset in the time domain relative to the respective neighbouring sample points of the filter; and iii) the neighbouring sample points of the filter are applied to respective of the offset and neighbouring sample points of the signal.

The Data Recovery with Inverse Transformation (DRIT) comprises methods and systems for reversing transmission channel transfer function in order to achieve a direct recovery of original data from a received signal distorted by a transmission link.