Abstract:
A method and system for encoding a series of input digital signals in a higher order digital format, such as 16 bit, to a series of lower order digital signals such as 8 bit, and then recovering the original input signals with a greater accuracy than previously attainable is described. A distinct reduction in quantization noise is produced, making the system compatible with very high resolution audio equipment such as compact disks. For each input signal, a particular pair of complementary encoding and decoding transformations are selected from a set of numerous possible transformations. The transformations are nonlinear, with high resolutions near the origin and much lower resolutions further away. The high resolution range increases from table to table, while the absolute resolution within said ranges decreases. The value of each input signal is predicted from previous signals, and a differential quantity representing the prediction error is used in selecting the table for each signal. Overall quantization noise is significantly reduced by updating the table selections so that the differential quantity remains within the high resolution range. Identical decoding circuitry is provided in both the encoder and decoder to assure tracking between the two. An analog-to-digital conversion is provided at the input, with a reverse conversion at the output.
Abstract:
The quantizing resolution of an analog-to-digital converter is effectively enhanced for sinusoidal input signals by (a) sampling the signal at 90 degree intervals of the sinusoid; (b) establishing the input range of the converter to be less than the dynamic range of the signal but arranged so that at least three of four successive samples are true or correct values; (c) detecting the occurrence of saturated fourth sample values; (d) calculating correct values for saturated sample values from preceding samples; and (e) substituting calculated values for saturated incorrect values.
Abstract:
A sensor device includes an A/D converter including an adder that computes a difference between an analog input signal and a predicted value, the adder includes a capacitive adder defined by a series circuit including a capacitive charge output device and a capacitor. A capacitive component in the charge output device defines a portion of the capacitance of the capacitive adder. A digital prediction filter generates the predicted value based on an output from a quantizer. The capacitive adder computes the difference between the analog input signal from the charge output device and the predicted value. The quantizer quantizes and encodes the difference. The A/D converter performs a Δ modulation on the analog input signal which is converted into a digital signal.
Abstract:
A predictive sensor readout is suitable for coupling to a sensor. The predictive sensor readout includes a sampling circuit, a predictor, and a preset circuit. The sampling circuit is configured to receive and over-sample previously digitized samples of signals previously input from the sensor. The predictor is coupled to the sampling circuit and is configured to receive the over-sampled digitized samples into a signal history and to generate a predicted input from the sensor based on the signal history. The preset circuit is coupled to the predictor and the sampling circuit and is configured to present the sampling circuit to receive the predicted input from the sensor prior to sampling an actual input from the sensor.
Abstract:
Predictive Analog-to-Digital Converter system in one embodiment includes a sampling section producing a sampled analog input signal with a first summer section combining the sampled analog input signal and an analog prediction signal to produce an analog prediction error signal. There is at least one error analog-to-digital convertor digitizing the analog prediction error signal, wherein a digital error signal output from the error analog-to-digital convertor is one of a full bitwidth error signal during an over-range condition else a lower bitwidth error signal. A second summer is coupled to the digital error signal output and a digital prediction signal, and generates a full bitwidth digital output signal. A feedback section is coupled to the digital output signal and providing the digital prediction signal and the analog prediction signal.
Abstract:
An analog-to-digital converter (“ADC”) architecture as described herein utilizes a digital signal processor having suitably configured waveform prediction logic that can predict expected types of input signals. The ADC architecture subtracts the predictable signal components from the analog input signal prior to the analog-to-digital conversion, which extends the dynamic range of the ADC employed by the ADC architecture. In practice, the ADC architecture can subtract predictable strong signal components from an analog input signal such that the ADC can apply its available dynamic range to the remaining weak signal components.
Abstract:
When converting an analog signal to N-bit digital codes, high SNR (signal to noise ratio) by generating multiple N-bit codes from the same analog sample and averaging the N-bit codes. However, the entire N-bit code is determined only a single time, and only P-bit (P less than N) codes are generated. The P-bit codes may be averaged, and the N-bit code is corrected based on the average value to generate an accurate N-bit digital code. As P can be much less than N, the correction can be implemented in a few iterations, thereby enabling the ADCs to be implemented with a high throughput performance. Due to the correction, a high SNR may be attained as well.
Abstract:
A data acquisition system uses an analog-to-digital converter (ADC) that includes a prediction feedback element. Using the computing power of a digital signal processor, the system predicts the next sample of the target signal based on pre-defined rules and previous samples. This digital prediction is converted to an analog signal using a digital-to-analog converter (DAC). An analog error summer compares the predicted signal with the target signal and creates an error signal. The digital signal processor uses the prediction error to more accurately predict the next sample. A negative feedback loop is thus formed by this system to drive the prediction error toward zero. Operating on the relatively small error signal in the forward and feedback paths enhances the conversion performance and data transfer efficiency.
Abstract:
A new signal processing method and a signal processing engine which can achieve extremely fast responsiveness to instantaneous changes in the behavior of the signal, and maintain the accuracy of standard harmonic methods. The signal processing engine unifies Nyquist's theorem and Taylor's theorem by means of polynomial approximations using linear operators, e.g. differential and integral operators. The signal processing engine samples the signal at a rate which is n times the band limit of the signal, where n is greater than 2, i.e. greater than the Nyquist rate, produces a digital representation of the sampled signal, and calculates the outputs of linear operators applied to polynomial approximations of the sampled signal. A switch mode power amplifier which incorporates the signal processing method and engine of the overcomes shortcomings of existing switching amplifiers, e.g. class "D" amplifiers. These shortcomings include: poor handling of highly reactive complex loads (e.g., speakers), usually requiring a duty cycle or feed-back adjustment with the change of the load; poor performance in the upper part of the bandwidth, including numerous switching artifacts; and high distortion, especially in the upper part of the spectrum. These shortcomings are all overcome using the local signal behavior signal processing method and engine of the invention.
Abstract:
Apparatus and an associated method are described for encoding an analog signal to a digital representation thereof and then decoding the same to reconstruct the original analog signal with reduced quantization noise and error. The analog signal is first adaptively pre-emphasized. A series of samples of the pre-emphasized signal are then obtained and encoded to create a series of digital representations which have a lower order resolution than the samples. The difference between each sample and its corresponding lower resolution digital representation is obtained and combined with the next sample. Decoding of the combined signals takes place in a complementary manner to create an approximate analog output signal, which is then de-emphasized in a manner complementary to the pre-emphasis to produce an analog output signal closely approximating the original analog signal. In a fully digital implementation the samples are converted to a digital format with a higher order resolution; the digital representations are obtained from the digitized samples, and the difference measurements are combined with the samples in their digital format. In a hybrid digital/analog implementation the difference is combined with the analog signal prior to sampling.