Samsung Electronics Co., Ltd.

Korea Advanced Institute of Science and Technology

Sangwon Ha

Sanghoon Park

Junhaeng Lee

Younoh Chi

Sungjin Kim

Dongil Son

Seungwon Lee

Kyungho Lee

Donghyun Lee

Seyoung Jang

Soohyun Seo

Hyunmo Yang

Gunhee Kim

Wonjo Lee

Yongjin Woo

Yeomoon Yoon

Subyung Kang

Jungmin Park

Jongwon Lee

Sungchul Park

Dongjin Park

Chulwoo Park

Junwhon Uhm

Yonghyun Park

Chonghwa Seo

Jinsub Kim

Seungkyu Choi

Yongwon Lee

Sungwon Park

Lee-Sup Kim

Yeonkyung Chung

Sungook Ok

Yongjune Park

Jaekang Shin

SeungWon Lee

A printed circuit board and/or an electronic device including the same are provided. The printed circuit board and/or an electronic device includes at least one insulation layer including a first rigid region and a flexible region extending from the first rigid region, at least one first circuit pattern disposed on one surface of the at least one insulation layer to at least partially transverse the flexible region from the first rigid region, and at least one conductive pad formed at least partially on a surface of the first circuit pattern in the first rigid region, wherein the flexible region may be configured to flexibly deform more than the first rigid region.

Printed circuit board, fabrication method of the same and electronic device including the same

A method of generating a fixed-point quantized neural network includes analyzing a statistical distribution for each channel of floating-point parameter values of feature maps and a kernel for each channel from data of a pre-trained floating-point neural network, determining a fixed-point expression of each of the parameters for each channel statistically covering a distribution range of the floating-point parameter values based on the statistical distribution for each channel, determining fractional lengths of a bias and a weight for each channel among the parameters of the fixed-point expression for each channel based on a result of performing a convolution operation, and generating a fixed-point quantized neural network in which the bias and the weight for each channel have the determined fractional lengths.

Method and apparatus for generating fixed-point quantized neural network

An electronic device is provided. The electronic device includes a housing, a first printed circuit board disposed in an internal space of the housing and including first conductive terminals, and a second printed circuit board disposed parallel to the first printed circuit board in the internal space and including second conductive terminals electrically connected to the first conductive terminals. The second printed circuit board includes at least some conductive terminals of the second conductive terminals, or at least one connection failure prevention structure disposed around at least some conductive terminals of the second conductive terminals.

Electronic device including interposer

A neural network data quantizing method includes: obtaining local quantization data by firstly quantizing, based on a local maximum value for each output channel of a current layer of a neural network, global recovery data obtained by recovering output data of an operation of the current layer based on a global maximum value corresponding to a previous layer of the neural network; storing the local quantization data in a memory to perform an operation of a next layer of the neural network; obtaining global quantization data by secondarily quantizing, based on a global maximum value corresponding to the current layer, local recovery data obtained by recovering the local quantization data based on the local maximum value for each output channel of the current layer; and providing the global quantization data as input data for the operation of the next layer.

Method and apparatus with neural network data quantizing

An electronic device is provided, which includes a PCB including a first alignment mark formed on a first surface of the PCB, and an RFPCB including a plurality of layers, a rigid portion disposed on the first surface of the PCB, a flexible portion extending from the rigid portion, and a first protrusion formed as one of the plurality of layers protruding and extending from the rigid portion. A second alignment mark corresponding to the first alignment mark of the PCB is defined in the first protrusion. The first protrusion overlaps at least partially with the first alignment mark of the PCB.

Rigid flexible printed circuit board and electronic device including the same

An electronic device is provided that includes a first circuit board including a first electronic component and a second electronic component disposed on a side of the first circuit board, a second circuit board spaced apart from the first circuit board and having a side facing the side of the first circuit board on which the first electronic component and the second electronic component are disposed, a first interposer disposed between the first circuit board and the second circuit board to form an inner space between the first circuit board and the second circuit board, and a second interposer disposed between the first circuit board and the second circuit board to divide the inner space into a first region and a second region, and wherein the first interposer and the second interposer electrically connect the first circuit board to the second circuit board.

A neural network method of parameter quantization obtains channel profile information for first parameter values of a floating-point type in each channel included in each of feature maps based on an input in a first dataset to a floating-point parameters pre-trained neural network, and determines a probability density function (PDF) type, for each channel, appropriate for the channel profile information based on a classification network receiving the channel profile information as a dataset. The neural network method of parameter quantization determines a fixed-point representation, based on the determined PDF type, for each channel, statistically covering a distribution range of the first parameter values, and generates a fixed-point quantized neural network based on the fixed-point representation determined for each channel.

Neural network method and apparatus with parameter quantization

A method of processing a neural network, includes generating an integral map for each channel in a first layer of the neural network based on calculating of area sums of pixel values in first output feature maps of channels in the first layer, generating an accumulated integral map by performing an accumulation operation on the integral maps generated for the respective channels, obtaining pre-output feature maps of a second layer, subsequent to the first layer, by performing a convolution operation between input feature maps of the second layer and weight kernels, and removing offsets in the weight kernels to obtain second output feature maps of the second layer by subtracting accumulated values of the accumulated integral map from pixel values of the pre-output feature maps.

Method and apparatus with neural network processing

Provided is a cable device having an improved electromagnetic interference (EMI) shielding performance. The cable device includes: a cable including an optical fiber; a connector including a printed circuit board connected to the cable and including a ground electrode, and a conductive case; a connecting member provided around a connection between the cable and the connector; and a metal shell surrounding the cable inside of the connecting member, the metal shell being configured to shield electromagnetic interference of the cable and the connector.

Electrical cable device with telescoping shielding features

A processor-implemented neural network method includes: determining a respective probability density function (PDF) of normalizing a statistical distribution of parameter values, for each channel of each of a plurality of feature maps of a pre-trained neural network; determining, for each channel, a corresponding first quantization range for performing quantization of corresponding parameter values, based on a quantization error and a quantization noise of the respective determined PDF; determining, for each channel, a corresponding second quantization range, based on a signal-to-quantization noise ratio (SQNR) of the respective determined PDF; correcting, for each channel, the corresponding first quantization range based on the corresponding second quantization range; and generating a quantized neural network, based on the corrected first quantization range corresponding for each channel.

Method and apparatus with neural network parameter quantization

A substrate connection member according to various embodiments of the present invention can comprise a printed circuit board which has a plurality of layers that are stacked and which comprises a front surface, a rear surface, and a side surface encompassing the front surface and the rear surface. The printed circuit board can comprise: an opening part which encompasses a partial region of the printed circuit board and which is penetratingly formed from the front surface to the rear surface; at least one bridge connected between the partial region and the printed circuit board by crossing at least a portion of the opening part; and at least one through-hole wire formed in the partial region from the front surface to the rear surface, wherein the inner surface of the opening part and the side surface of the bridge can be formed from a conductive member. Other various embodiments, in addition to the embodiments disclosed in the present invention, are possible.

Substrate connection member comprising substrate having opening part, which encompasses region in which through wire is formed, and conductive member formed on side surface of opening part, and electronic device comprising same

An electronic device includes a communication circuit electrically connected with a circuit board. The circuit board includes a first portion comprising a first layered structure in which a wiring layer and a first insulating layer are alternately positioned, and a second portion comprising a second layered structure in which the wiring layer and the first insulating layer are alternately positioned and a second insulating layer. At least one antenna patch is positioned on or within the second insulating layer. A conductive line penetrates the second layered structure and the second insulating layer and electrically connects the at least one antenna patch and the communication circuit. The first insulating layer has a first loss tangent value, and the second insulating layer has a second loss tangent value smaller than the first loss tangent value.

Circuit board including insulating layer having a plurality of dielectrics with different dielectric loss, and electronic device including the circuit board

Growing community of inventors

Seongnam-si, South Korea

Sangwon Ha