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At least 271 records · Page 15

Loss tolerant speech decoder for telecommunications

A method and device for extrapolating past signal-history data for insertion into missing data segments in order to conceal digital speech frame errors. The extrapolation method uses past-signal history that is stored in a buffer. The method is implemented with a device that utilizes a finite-impulse response (FIR) multi-layer feed-forward artificial neural network that is trained by back-propagation for one-step extrapolation of speech compression algorithm (SCA) parameters. Once a speech connection has been established, the speech compression algorithm device begins sending encoded speech frames. As the speech frames are received, they are decoded and converted back into speech signal voltages. During the normal decoding process, pre-processing of the required SCA parameters will occur and the results stored in the past-history buffer. If a speech frame is detected to be lost or in error, then extrapolation modules are executed and replacement SCA parameters are generated and sent as the parameters required by the SCA. In this way, the information transfer to the SCA is transparent, and the SCA processing continues as usual. The listener will not normally notice that a speech frame has been lost because of the smooth transition between the last-received, lost, and next-received speech frames.

Prieto, Jr., Jaime L.↗

Iterative Demodulation and Decoding of Non-Square QAM

It has been shown that a non-square (NS) 2(sup 2n+1)-ary (where n is a positive integer) quadrature amplitude modulation [(NS)2(sup 2n+1)-QAM] has inherent memory that can be exploited to obtain coding gains. Moreover, it should not be necessary to build new hardware to realize these gains. The present scheme is a product of theoretical calculations directed toward reducing the computational complexity of decoding coded 2(sup 2n+1)-QAM. In the general case of 2(sup 2n+1)-QAM, the signal constellation is not square and it is impossible to have independent in-phase (I) and quadrature-phase (Q) mapping and demapping. However, independent I and Q mapping and demapping are desirable for reducing the complexity of computing the log likelihood ratio (LLR) between a bit and a received symbol (such computations are essential operations in iterative decoding). This is because in modulation schemes that include independent I and Q mapping and demapping, each bit of a signal point is involved in only one-dimensional mapping and demapping. As a result, the computation of the LLR is equivalent to that of a one-dimensional pulse amplitude modulation (PAM) system. Therefore, it is desirable to find a signal constellation that enables independent I and Q mapping and demapping for 2(sup 2n+1)-QAM.

Li, Lifang↗

Frame Decoder for Consultative Committee for Space Data Systems (CCSDS)

GNU Radio is a free and open source development toolkit that provides signal processing to implement software radios. It can be used with low-cost external RF hardware to create software defined radios, or without hardware in a simulation-like environment. GNU Radio applications are primarily written in Python and C++. The Universal Software Radio Peripheral (USRP) is a computer-hosted software radio designed by Ettus Research. The USRP connects to a host computer via high-speed Gigabit Ethernet. Using the open source Universal Hardware Driver (UHD), we can run GNU Radio applications using the USRP. An SDR is a "radio in which some or all physical layer functions are software defined"(IEEE Definition). A radio is any kind of device that wirelessly transmits or receives radio frequency (RF) signals in the radio frequency. An SDR is a radio communication system where components that have been typically implemented in hardware are implemented in software. GNU Radio has a generic packet decoder block that is not optimized for CCSDS frames. Using this generic packet decoder will add bytes to the CCSDS frames and will not permit for bit error correction using Reed-Solomon. The CCSDS frames consist of 256 bytes, including a 32-bit sync marker (0x1ACFFC1D). This frames are generated by the Space Data Processor and GNU Radio will perform the modulation and framing operations, including frame synchronization.

Reyes, Miguel A. De Jesus↗

Controller area network decoder (CAN-D)

A system and method for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This technology can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system and method can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

Coupled receiver-decoders

This paper describes coupled receiver-decoder architectures for suppressed carrier convolutionally-coded signals and residual carrier turbo-coded signals.

convolutional codes turbo codes receiver decoder j↗

Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-variant encoder–decoder (ED) model designed specifically to improve multi-step reservoir inflow forecasting, enabling accurate predictions of reservoir inflows up to seven days ahead. Unlike conventional ED-LSTM and recursive ED-LSTM models, which use fixed encoder parameters or recursively propagate predictions, our model incorporates an adaptive encoder structure that dynamically adjusts to evolving conditions at each forecast horizon. Additionally, we introduce the Expected Baseline Integrated Gradients (EB-IGs) method for variable importance analysis, enhancing interpretability of inflow by incorporating multiple baselines to capture a broader range of hydrometeorological conditions. The proposed methods are demonstrated at several diverse reservoirs across the United States. Our results show that they outperform traditional methods, particularly at longer lead times, while also offering insights into the key drivers of inflow forecasting. These advancements contribute to enhanced reservoir management through improved forecasting accuracy and practical decision-making insights under complex hydroclimatic conditions.

58 GEOSCIENCES↗

Iterative demodulation and decoding of coded non-square QAM

Simulation results show that, with iterative demodulation and decoding, coded NS-8QAM performs 0.5 dB better than standard 8QAM and 0.7 dB better than 8PSK at BER= 10(sup -5), when the FEC code is the (15, 11) Hamming code concatenated with a rate-1 accumulator code, while coded NS-32QAM performs 0.25 dB better than standard 32QAM.

iterative decoding QAM bit error rate capacity↗