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512MILFT
+Lista de MateriaisIC CLK MULTIPLIER PLL 8-SOIC
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FabricanteRenesas Electronics America Inc.
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Peça do Fabricante #512MILFT
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Pacote SOIC-8
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Em Estoque5958
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Especificações
| Atributo | Valor |
| Package / Case | Tape & Reel (TR),Cut Tape (CT) |
| Series | LOCO™ |
| Part Status | Obsolete |
| Type | Clock Generator |
| PLL | Yes with Bypass |
| Input | Clock, Crystal |
| Output | CMOS |
| Number of Circuits | 1 |
| Ratio - Input: Output | 1:2 |
| Differential - Input: Output | No/No |
| Frequency - Max | 160MHz |
| Divider / Multiplier | No/Yes |
| Voltage - Supply | 3V ~ 5.5V |
| Operating Temperature | -40°C ~ 85°C |
| Mounting Type | Surface Mount |
Visão Geral
Equivalent
- Cypress CY7C1041DV33: 512K x 8, 3.3V
- ISSI IS61LV5128: 512K x 8, 3.3V
- Renesas 71V124SA: 128K x 8, 3.3V (similar density)
- Micron MT45W8MW16BGX: 8Mb x 16 (if higher density needed)
Check voltage, pinout, and timing for compatibility.
Features
1. Compact Representation: Uses 512D embeddings for lightweight yet effective feature extraction.
2. Multiple Instance Learning (MIL): Processes bags of instances (e.g., image patches) for weakly supervised tasks like classification.
3. Efficiency: Balances performance and computational cost, suitable for resource-constrained environments.
4. Versatility: Applicable to medical imaging (e.g., histopathology), satellite imagery, and other patch-based analyses.
5. Weak Supervision: Trains with bag-level labels, reducing annotation effort.
It’s ideal for tasks requiring fine-grained analysis without heavy computational overhead.
Pinout
- Pin Count: 48 pins (typically in a TSOP (Thin Small Outline Package) or similar form factor).
- Key Functions:
- Parallel Interface: Supports high-speed read/write operations.
- Voltage Range: Typically 3V operation.
- Dual Boot Support: Allows flexible memory partitioning.
- Sector Erase: Configurable erase blocks (e.g., 4KB, 32KB, 64KB).
- Asynchronous/Synchronous Modes: For compatibility with different systems.
It is commonly used in embedded systems, networking equipment, and industrial applications.
Manufacturer
Application
1. Edge Computing: Lightweight inference on low-memory devices.
2. IoT: Real-time data processing for sensors and smart devices.
3. Embedded Systems: Integration into resource-constrained hardware.
4. Basic Computer Vision: Simple object detection or classification tasks.
5. Education/Training: Low-cost AI experimentation for students.
Suitable for scenarios where model size and speed are prioritized over high accuracy.