Abstract: An audio encoding/decoding apparatus and method using vector quantized residual error features are disclosed. An audio signal encoding method includes outputting a bitstream of a main codec by encoding an original signal, decoding the bitstream of the main codec, determining a residual error feature vector from a feature vector of a decoded signal and a feature vector of the original signal, and outputting a bitstream of additional information by encoding the residual error feature vector.

Abstract: A method of rendering object-based audio and an electronic device for performing the method are disclosed. The method includes identifying metadata of the object-based audio, determining whether the metadata includes a parameter set for an atmospheric absorption effect for each distance, and rendering the object-based audio, using a distance between the object-based audio and a listener obtained using the metadata and the atmospheric absorption effect according to an effect of a medium attenuation based on the parameter, when the metadata includes the parameter.

Abstract: Provided are an electrolyte for a rechargeable lithium battery and a rechargeable lithium battery including same, the electrolyte including a nonaqueous organic solvent, a lithium salt, and an additive, wherein the additive is a composition comprising a first compound represented by Chemical Formula 1 and a second compound represented by Chemical Formula 2. The details of Chemical Formulas 1 and 2 are as set forth in the specification.

Abstract: A signal compression method and apparatus and a signal restoration method and apparatus are provided. The signal compression method includes outputting an input signal, obtained by processing an audio signal, which is input, based on a human auditory perception characteristic, using an auditory perception model, extracting a feature vector from the input signal using a feature extraction module, and outputting a code obtained by compressing the feature vector using a trained signal compression model.

Abstract: A method and apparatus for processing an audio signal are disclosed. According to an example embodiment, a method of processing an audio signal may include acquiring a final audio signal for an initial audio signal using a plurality of neural network models generating output audio signals by encoding and decoding input audio signals, calculating a difference between the initial audio signal and the final audio signal in a time domain, converting the initial audio signal and the final audio signal into Mel-spectra, calculating a difference between the Mel-spectra of the initial audio signal and the final audio signal in a frequency domain, training the plurality of neural network models based on results calculated in the time domain and the frequency domain, and generating a new final audio signal distinguished from the final audio signal from the initial audio signal using the trained neural network models.

Abstract: A method of rendering object audio and electronic device for performing the method are provided. The method includes identifying object audio and metadata including a reference distance of the object audio and an audio source distance between the object audio and a listener, identifying a maximum distance of the object audio determined based on the reference distance, when the audio source distance is less than or equal to the maximum distance, determining a gain of the object audio based on the audio source distance and the reference distance, and rendering the object audio according to the gain of the object audio.

Abstract: Disclosed are methods of encoding and decoding an audio signal using side information, and an encoder and a decoder for performing the methods. The method of encoding an audio signal using side information includes identifying an input signal, the input signal being an original audio signal, extracting side information from the input signal using a learning model trained to extract side information from a feature vector of the input signal, encoding the input signal, and generating a bitstream by combining the encoded input signal and the side information.

Abstract: Provided are an electrolyte for a rechargeable lithium battery and a rechargeable lithium battery including same, the electrolyte including a non-aqueous organic solvent, a lithium salt, and an additive, wherein the additive is a composition including a first compound represented by Chemical Formula 1 and a second compound represented by Chemical Formula 2. Details of Chemical Formulas 1 and 2 are the same as those described in the specification.

Abstract: An encoding method, a decoding method, an encoder for performing the encoding method, and a decoder for performing the decoding method are provided. The encoding method includes outputting LP coefficients bitstream and a residual signal by performing an LP analysis on an input signal, outputting a first latent signal obtained by encoding a periodic component of the residual signal, a second latent signal obtained by encoding a non-periodic component of the residual signal, and a weight vector for each of the first latent signal and the second latent signal, using a first neural network module, and outputting a first bitstream obtained by quantizing the first latent signal, a second bitstream obtained by quantizing the second latent signal, and a weight bitstream obtained by quantizing the weight vector, using a quantization module.

Abstract: Provided are an additive represented by Chemical Formula 1, an electrolyte for a lithium secondary battery including the same, and a lithium secondary battery. The details of Chemical Formula 1 are as set forth in the specification.

Abstract: Disclosed are a positive electrode for a rechargeable lithium battery and a rechargeable lithium battery including the same. For example, one or more embodiments provide a positive electrode for a rechargeable lithium battery including a positive electrode current collector and a positive electrode active material layer on one surface or two opposing surfaces of the positive electrode current collector, wherein the positive electrode active material layer includes a metal organic framework of ZIF-8, MOF-177, HKUST-1, Fe-BTC, or a combination thereof; and a positive electrode active material that is a nickel-based oxide.

Abstract: An apparatus and method for pitch-shifting an audio signal with low complexity are disclosed. The method includes identifying a distance between an audio object included in the audio signal and a listener, checking whether the distance between the audio object and the listener decreases, and performing stepwise stretching pitch-shifting of repeatedly using at least one of frequency components of the audio signal when the distance between the audio object and the listener decreases.

Abstract: An audio signal processing apparatus and an audio signal processing method are disclosed. The audio signal processing method performed by the audio signal processing apparatus includes determining whether a line of sight between a render item (RI) corresponding to an audio element and a listener is visible, based on a bitstream, in response to a case where the line of sight is invisible, generating an audio signal by rendering a diffraction-type RI corresponding to the RI, and outputting the audio signal.

Abstract: Provided are an electrolyte for a rechargeable lithium battery and a rechargeable lithium battery including the same, the electrolyte including a nonaqueous organic solvent, a lithium salt, and an additive, wherein the additive is a composition including a first compound represented by Chemical Formula 1 and a second compound represented by Chemical Formula 2, the first compound and the second compound are included in an amount of 0.1 to 10 wt%, respectively. Details of Chemical Formulas 1 and 2 are the same as those described in the specification.

Abstract: An encoding apparatus extracts features of an image by applying multiple padding operations and multiple downscaling operations to an image represented by data and transmits feature information indicating the features to a decoding apparatus. The multiple padding operations and the multiple downscaling operations are applied to the image in an order in which one padding operation is applied and thereafter one downscaling operation corresponding to the padding operation is applied. A decoding method receives feature information from an encoding apparatus, and generates a reconstructed image by applying multiple upscaling operations and multiple trimming operations to an image represented by the feature information. The multiple upscaling operations and the multiple trimming operations are applied to the image in an order in which one upscaling operation is applied and thereafter one trimming operation corresponding to the upscaling operation is applied.

Abstract: An encoding method and an encoding device using a complex signal and a decoding method and a decoding device using a complex signal are provided. The encoding method includes converting a first channel signal and a second channel signal constituting an audio signal corresponding to a stereo signal from a real domain to a complex domain, determining one of a sum operation, a difference operation, and a bypass operation to be performed on the second channel signal converted to the complex domain, determining a complex spatial cue according to the determined operation, converting a residual signal for the second channel signal to a real domain using the complex spatial cue, converting the first channel signal to a real domain, encoding the first channel signal converted to the real domain, and encoding the residual signal for the second channel signal converted to the real domain.

Abstract: A method for encoding an input signal using N flow blocks (N is a natural number greater than or equal to 2) and (N?1) split block(s), which is performed by a processor, may comprise: transmitting, by a k-th flow block (k is a natural number greater than or equal to 1 and less than or equal to N?1) among the N flow blocks, a k-th transformation signal obtained by transforming a received signal into a latent representation to a k-th split block among the (N?1) split block(s); splitting, by the k-th split block, the k-th transformation signal by a predetermined ratio, into a first split signal and a second split signal; transmitting, by the k-th split block, the first split signal to a (k+1)-th flow block; and quantizing a signal transformed by an N-th flow block and the second split signals using a quantization block.

Abstract: An apparatus for controlling charging of an electric vehicle and a method therefor are provided. The apparatus includes a communication device that performs vehicle-to-everything (V2X) communication with a charging station management server outside the electric vehicle and a vehicle management server configured to manage shared vehicles and a processor that requests the charging station management server to reserve a charging station via the communication device and automatically requests the vehicle management server to reserve a shared vehicle to be used when the electric vehicle is charged, via the communication device, when a vehicle power for driving to a destination is insufficient.

Abstract: Disclosed herein is an encoding method. The encoding method includes extracting a feature map from an input image, determining an encoding feature map based on the extracted feature map, generating a converted feature map by performing conversion on the encoding feature map, and performing encoding on the converted feature map.

Abstract: Provided is a method and apparatus for designing and testing an audio codec using quantization based on white noise modeling. A neural network-based audio encoder design method includes generating a quantized latent vector and a reconstructed signal corresponding to an input signal by using a white noise modeling-based quantization process, computing a total loss for training a neural network-based audio codec, based on the input signal, the reconstruction signal, and the quantized latent vector, training the neural network-based audio codec by using the total loss, and validating the trained neural network-based audio codec to select the best neural network-based audio codec.